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ahong286286

ICML 2016 papers

Detailed Schedule

Monday – Neural Networks and Deep Learning

Session chair: Hugo Larochelle

Location:  Ballroom 1+2+Juliard
  • 10:20 – One-Shot Generalization in Deep Generative Models Danilo Rezende Google DeepMind, Shakir , Ivo Danihelka Google DeepMind, Karol Gregor DeepMind, Daan Wierstra Google DeepMindPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – Learning to Generate with Memory Chongxuan Li Tsinghua University, Jun Zhu Tsinghua, Bo Zhang Tsinghua UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – A Theory of Generative ConvNet Jianwen Xie UCLA, Yang Lu UCLA, Song-Chun Zhu UCLA, Yingnian Wu UCLAPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Deconstructing the Ladder Network Architecture Mohammad Pezeshki Universite de Montreal, Linxi Fan , Philemon Brakel , Aaron Courville , Yoshua Bengio U. of MontrealPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks Devansh ArpitSUNY Buffalo, Yingbo Zhou SUNY Buffalo, Bhargava Kota SUNY Buffalo, Venu Govindaraju SUNY BuffaloPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – Unitary Evolution Recurrent Neural Networks Martin Arjovsky University of Buenos Aires, Amar Shah University of Cambridge, Yoshua BengioPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    Session chair: Honglak Lee

    Location:  Ballroom 1+2+Juliard
  • 02:00 – Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin Dario Amodei , Rishita Anubhai , Eric Battenberg , Carl Case , Jared Casper , Bryan Catanzaro , JingDong Chen , Mike Chrzanowski Baidu USA, Inc., Adam Coates , Greg Diamos Baidu USA, Inc., Erich Elsen Baidu USA, Inc., Jesse Engel , Linxi Fan , Christopher Fougner , Awni Hannun Baidu USA, Inc., Billy Jun , Tony Han , Patrick LeGresley , Xiangang Li Baidu, Libby Lin , Sharan Narang , Andrew Ng , Sherjil Ozair , Ryan Prenger , Sheng Qian Baidu, Jonathan Raiman , Sanjeev SatheeshBaidu SVAIL, David Seetapun , Shubho Sengupta , Chong Wang , Yi Wang , Zhiqian Wang , Bo Xiao , Yan Xie Baidu, Dani Yogatama , Jun Zhan , zhenyao ZhuPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Persistent RNNs: Stashing Recurrent Weights On-Chip Greg Diamos Baidu USA, Inc., Shubho Sengupta Baidu USA, Inc., Bryan Catanzaro Baidu USA, Inc., Mike Chrzanowski Baidu USA, Inc., Adam Coates , Erich Elsen Baidu USA, Inc., Jesse Engel Baidu USA, Inc., Awni Hannun Baidu USA, Inc., Sanjeev Satheesh Baidu USA, Inc.Paper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Sequence to Sequence Training of CTC-RNNs with Partial Windowing Kyuyeon Hwang Seoul National University, Wonyong SungSeoul National UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – Analysis of Deep Neural Networks with Extended Data Jacobian Matrix Shengjie Wang University of Washington, Abdel-rahman Mohamed , Rich Caruana Microsoft, Jeff Bilmes U. of Washington, Matthai Plilipose , Matthew Richardson , Krzysztof Geras , Gregor Urban UC Irvine, Ozlem AslanPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units Wenling Shang , Kihyuk Sohn NEC Laboratories America, Diogo Almeida Enlitic, Honglak Lee University of MichiganPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • Best paper award – 03:44 – Pixel Recurrent Neural Networks Aaron Van den Oord Google Deepmind, Nal Kalchbrenner Google Deepmind, Koray Kavukcuoglu Google DeepmindPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Reinforcement Learning

    Session chair: Joelle Pineau

    Location:  Ballroom 3+4
  • 10:20 – Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well Ozgur Simsek , Simon Algorta , Amit KothiyalPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – Opponent Modeling in Deep Reinforcement Learning He He , Jordan , Kevin Kwok Massachusetts Institute of Technology, Hal Daume MarylandPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – Control of Memory, Active Perception, and Action in Minecraft Junhyuk Oh University of Michigan, Valliappa ChockalingamUniversity of Michigan, Satinder , Honglak Lee University of MichiganPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Graying the black box: Understanding DQNs Tom Zahavy Technion, Nir Ben-Zrihem , Shie Mannor TechnionPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Benchmarking Deep Reinforcement Learning for Continuous Control Yan Duan University of California, Berk, Xi Chen University of California, Berkeley, Rein Houthooft Ghent University, John Schulman University of California, Berkeley, Pieter Abbeel BerkeleyPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • Best paper award – 12:04 – Dueling Network Architectures for Deep Reinforcement Learning Ziyu Wang Google Inc., Tom Schaul Google Inc., Matteo Hessel Google Deepmind, Hado van Hasselt Google DeepMind, Marc Lanctot Google Deepmind, Nando de Freitas University of OxfordPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Monday – Optimization (Continuous)

    Session chair: Sebastien Bubeck

    Location:  Marquis
  • 10:20 – SDCA without Duality, Regularization, and Individual Convexity Shai Shalev-Shwartz Hebrew University of JerusalemPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Carnegie Mellon University, Ahmed Hefny , Suvrit Sra, Barnabas Poczos , AlexPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – Fast Rate Analysis of Some Stochastic Optimization Algorithms Chao Qu Nus, Huan Xu National University of Singapore, Chong jin Ong NusPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Black-box Optimization with a Politician Sebastien Bubeck Microsoft, Yin Tat Lee MITPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Starting Small – Learning with Adaptive Sample Sizes Hadi Daneshmand ETH Zurich, Aurelien Lucchi ETHZ, Thomas HofmannPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – Primal-Dual Rates and Certificates Celestine Dünner IBM Research, Simone Forte Google, Martin Takac , Martin JaggiPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Monday – Online Learning

    Session chair: Alina Beygelzimer

    Location:  Lyceum
  • 10:20 – Online Learning with Feedback Graphs Without the Graphs Alon Cohen Technion, Tamir Hazan , Tomer KorenPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – Efficient Algorithms for Adversarial Contextual Learning Vasilis Syrgkanis Microsoft Research, Akshay Krishnamurthy Microsoft Research, Robert Schapire Microsoft ResearchPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits Alexander Rakhlin , Karthik Sridharan CornellPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Online Stochastic Linear Optimization under One-bit Feedback Lijun Zhang Nanjing University, Tianbao Yang University of Iowa, Rong Jin Alibaba Group, Yichi Xiao Nanjing University, Zhi-hua ZhouPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient Tianbao YangUniversity of Iowa, Lijun Zhang Nanjing University, Rong Jin , Jinfeng Yi IBM ResearchPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – Adaptive Algorithms for Online Convex Optimization with Long-term Constraints Rodolphe Jenatton , Jim Huang Amazon, Cedric ArchambeauPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    Session chair: Csaba Szepesvari

    Location:  Liberty
  • 04:15 – Pricing a Low-regret Seller Hoda Heidari , Mohammad Mahdian Google, Umar Syed , Sergei Vassilvitskii , Sadra Yazdanbod Georgia Institute of TechnologyPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Multi-Player Bandits — a Musical Chairs Approach Jonathan Rosenski Weizmann Institute of Science, Ohad Shamir Weizmann Institute of Science, Liran Szlak Weizmann Institute of SciencePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Contextual Combinatorial Cascading Bandits Shuai Li CUHK, Baoxiang Wang , Shengyu Zhang , Wei ChenPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm Junpei Komiyama The University of Tokyo, Junya Honda The University of Tokyo, Hiroshi Nakagawa The University of TokyoPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – DCM Bandits: Learning to Rank with Multiple Clicks Sumeet Katariya University of Wisconsin Madiso, Branislav Kveton Adobe Research, Csaba Szepesvari Alberta, Zheng WenPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Distributed Clustering of Linear Bandits in Peer to Peer Networks Nathan Korda University of Oxford, Balazs Szorenyi , Shuai LiUniversity of InsubriaPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Clustering

    Session chair: Alexandru Niculescu-Mizil

    Location:  Empire
  • 10:20 – Correlation Clustering and Biclustering with Locally Bounded Errors Gregory Puleo UIUC, Olgica Milenkovic UIUCPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 –  K K-Means Clustering with Distributed Dimensions Hu Ding State University of New York at Buffalo, Yu Liu Tsinghua University, IIIS, Lingxiao Huang , Jian LiPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – Speeding up k-means by approximating Euclidean distances via block vectors Thomas Bottesch Ulm University, Thomas BühlerAvira, Markus Kächele Ulm UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Fast k-means with accurate bounds James Newling Idiap Research Institute, Francois Fleuret Idiap research institutePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – k-variates++: more pluses in the k-means++ Richard Nock Nicta & ANU, Raphael Canyasse Ecole Polytechnique and The Technion, Roksana Boreli Data61, Frank Nielsen Ecole Polytechnique and Sony CS Labs Inc.Paper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – Compressive Spectral Clustering Nicolas TREMBLAY INRIA Rennes, Gilles Puy Technicolor, Remi Gribonval INRIA, Pierre Vandergheynst EPFLPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Monday – Bayesian Nonparametric Methods

    Session chair: Hal Daume III

    Location:  Soho
  • 10:20 – On collapsed representation of hierarchical Completely Random Measures Gaurav Pandey Indian Institute of Science, Ambedkar Dukkipati Indian Institute of SciencePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – Hawkes Processes with Stochastic Excitations Young Lee NICTA, Kar Wai Lim ANU, Cheng Soon Ong NICTAPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM Ardavan Saeedi MIT, Matthew Hoffman Adobe Research, Matthew Johnson , Ryan Adams HarvardPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Markov Latent Feature Models Aonan Zhang Columbia University, John PaisleyPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Diversity-Promoting Bayesian Learning of Latent Variable Models Pengtao Xie Carnegie Mellon University, Jun Zhu Tsinghua, Eric Xing CMUPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations Aaron Schein , Mingyuan Zhou , Blei David Columbia, Hanna Wallach MicrosoftPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Monday – Matrix Factorization / Neuroscience Applications

    Session chair: Jennifer Dy

    Location:  Liberty
  • 10:20 – The knockoff filter for FDR control in group-sparse and multitask regression Ran Dai The University of Chicago, Rina Barber The University of ChicagoPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:37 – A Simple and Provable Algorithm for Sparse Diagonal CCA Megasthenis Asteris University of Texas at Austin, Anastasios Kyrillidis , Oluwasanmi Koyejo Stanford University & University of Illinois at Urbana Champaign, Russell Poldrack Stanford UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:54 – Experimental Design on a Budget for Sparse Linear Models and Applications Sathya Narayanan Ravi UW Madison, Vamsi IthapuUW Madison, Sterling Johnson UW Madison, Vikas SinghPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:30 – Representational Similarity Learning with Application to Brain Networks Urvashi Oswal University of Wisconsin, Christopher CoxUniversity of Wisconsin, Matthew Lambon-Ralph , Timothy Rogers University of Wisconsin, Robert NowakPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:47 – Dictionary Learning for Massive Matrix Factorization Arthur Mensch Inria, Julien Mairal , Bertrand Thirion Inria, Gael VaroquauxPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:04 – A Random Matrix Approach to Echo-State Neural Networks Romain Couillet CentraleSupelec, Gilles Wainrib ENS Ulm, Paris, France, Hafiz Tiomoko Ali CentraleSupelec, Gif-sur-Yvette, France, Harry Sevi ENS Lyon, Lyon, ParisPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Monday – Optimization / Online Learning

    Session chair: Satyen Kale

    Location:  Ballroom 3+4
  • 02:00 – Shifting Regret, Mirror Descent, and Matrices Andras Gyorgy , Csaba Szepesvari AlbertaPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Heteroscedastic Sequences: Beyond Gaussianity Oren , Shie Mannor TechnionPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Convergence of Stochastic Gradient Descent for PCA Ohad Shamir Weizmann Institute of SciencePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity Ohad Shamir Weizmann Institute of SciencePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber TTI Chicago, Elad Hazan Princeton University, Chi Jin UC Berkeley, Sham , Cameron Musco Massachusetts Institute of Technology, Praneeth Netrapalli Microsoft Research, Aaron SidfordMicrosoft Research, New EnglandPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – Solving Ridge Regression using Sketched Preconditioned SVRG Alon Gonen Hebrew University of Jerusalem, Francesco OrabonaYahoo, Shai Shalev-Shwartz Hebrew University of JerusalemPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Machine Learning Applications

    Session chair: Balazs Kegl

    Location:  Marquis
  • 02:00 – Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design William Hoiles UCLA, Mihaela van der SchaarPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Dealbreaker: A Nonlinear Latent Variable Model for Educational Data Andrew Lan Rice University, Tom Goldstein University of Maryland, Richard Baraniuk Rice University, Christoph Studer Cornell UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Estimating Cosmological Parameters from the Dark Matter Distribution Siamak Ravanbakhsh CMU, Junier Oliva CMU, Sebastian Fromenteau Carnegie Mellon Unitversity, Layne Price Carnegie Mellon Unitversity, Shirley Ho Carnegie Mellon Unitversity, Jeff Schneider Carnegie Mellon Unitversity, Barnabas PoczosPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces Shane Carr Washington University in St. L, Roman Garnett Wustl, Cynthia Lo Washington University in St. LouisPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Predictive Entropy Search for Multi-objective Bayesian Optimization Daniel Hernandez-Lobato , Jose miguel Hernandez-Lobato , Amar Shah University of Cambridge, Ryan Adams HarvardPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – Pareto Frontier Learning with Expensive Correlated Objectives Amar Shah University of Cambridge, ZoubinPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Matrix Factorization and Related Topics

    Session chair: Alex Kulesza

    Location:  Lyceum
  • 02:00 – Complex Embeddings for Simple Link Prediction Théo Trouillon Xerox, Johannes Welbl , Sebastian Riedel , Eric Gaussier , Guillaume BouchardPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – PAC learning of Probabilistic Automaton based on the Method of Moments Hadrien Glaude University of Lille, Olivier Pietquin Univ. Lille, CRIStAL, UMR 9189, SequeL Team, Villeneuve d’Ascq, 59650, FRANCEPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Rich Component Analysis Rong Ge , James ZouPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – Beyond CCA: Moment Matching for Multi-View Models Anastasia Podosinnikova INRIA – ENS, Francis Bach Inria, Simon Lacoste-Julien INRIAPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Isotonic Hawkes Processes Yichen Wang Georgia Tech, Bo Xie , Nan Du , Le Song GatechPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – Non-negative Matrix Factorization under Heavy Noise Chiranjib Bhattacharya , Navin Goyal Microsoft Research India, Ravindran Kannan Microsoft Reseach India, Jagdeep Pani Indian Institute of SciencePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Bandit Problems

    Session chair: Shie Mannor

    Location:  Empire
  • 02:00 – An optimal algorithm for the Thresholding Bandit Problem Andrea LOCATELLI University of Potsdam, Maurilio Gutzeit Universität Potsdam, Alexandra CarpentierPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Anytime Exploration for Multi-armed Bandits using Confidence Information Kwang-Sung Jun UW-Madison, Robert NowakPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Anytime optimal algorithms in stochastic multi-armed bandits Rémy Degenne Université Paris Diderot, Vianney PerchetPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – PAC Lower Bounds and Efficient Algorithms for The Max  K K-Armed Bandit Problem Yahel David Technion, Nahum ShimkinTechnionPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Conservative Bandits Yifan Wu , Roshan Shariff University of Alberta, Tor , Csaba Szepesvari AlbertaPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – No-Regret Algorithms for Heavy-Tailed Linear Bandits Andres Munoz Medina , Scott YangPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Graphical Models

    Session chair: Stefano Ermon

    Location:  Soho
  • 02:00 – Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams Roy Adams Univ. of Massachusetts-Amherst, Nazir Saleheen , Edison Thomaz , Abhinav Parate , Santosh Kumar , Benjamin MarlinPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model Xinze Guan Oregon State University, Raviv Raich Oregon State University, Weng-keenPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Clustering High Dimensional Categorical Data via Topographical Features Chao Chen CUNY, Novi Quadrianto University of SussexPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:10 – Nonlinear Statistical Learning with Truncated Gaussian Graphical Models Qinliang Su Duke University, xuejun Liao , changyou Chen , Lawrence CarinPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – Collapsed Variational Inference for Sum-Product Networks Han Zhao Carnegie Mellon University, Tameem Adel University of Amsterdam, Geoff Gordon CMU, Brandon Amos Carnegie Mellon UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies David Inouye University of Texas at Austin, Pradeep Ravikumar UT Austin, InderjitPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Transfer Learning / Learning Theory

    Session chair: Alina Beygelzimer

    Location:  Liberty
  • 02:00 – A New PAC-Bayesian Perspective on Domain Adaptation Pascal Germain INRIA, Amaury Habrard , François Laviolette GRAAL, Université Laval, Emilie MorvantPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:17 – Domain Adaptation with Conditional Transferable Components Mingming Gong University of Technology Sydne, Kun ZhangCarnegie Mellon University, Tongliang Liu MPI Tuebingen, Dacheng Tao , Clark Glymour , Bernhard SchölkopfPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 02:34 – Minimizing the Maximal Loss: How and Why Shai Shalev-Shwartz Hebrew University of Jerusalem, Yonatan Wexler OrcamPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 03:10 – Accurate Robust and Efficient Error Estimation for Decision Trees Lixin Fan Nokia TechnologiesPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:27 – The Teaching Dimension of Linear Learners Ji Liu University of Rochester, Xiaojin Zhu University of Wisconsin, Hrag OhannessianUniversity of Wisconsin-MadisonPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 03:44 – Loss factorization, weakly supervised learning and label noise robustness Giorgio Patrini ANU / Data61, Frank Nielsen Ecole Polytechnique and Sony CS Labs Inc., Richard Nock Nicta & ANU, Marcello Carioni Max Planck InstitutePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Neural Networks and Deep Learning I

    Session chair: Kyunghyun Cho

    Location:  Ballroom 1+2+Juliard
  • 04:15 – Texture Networks: Feed-forward Synthesis of Textures and Stylized Images Dmitry Ulyanov Skolkovo institute of science , Vadim Lebedev , Andrea , Victor Lempitsky Skolkovo Institute of Sci&TechPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Discrete Deep Feature Extraction: A Theory and New Architectures Thomas Wiatowski ETH Zurich, Michael Tschannen ETH Zurich, Aleksandar Stanic ETH Zurich, Philipp Grohs University of Vienna, Helmut Boelcskei ETH ZurichPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Deep Structured Energy Based Models for Anomaly Detection Shuangfei Zhai Binghamton University, Yu Cheng IBM Research, Weining Lu Tsinghua Univerisity, Zhongfei Zhang Binghamton UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Noisy Activation Functions Caglar Gülçehre , Marcin Moczulski , Misha Denil , Yoshua Bengio U. of MontrealPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – A Kronecker-factored approximate Fisher matrix for convolution layers Roger Grosse , James Martens University of TorontoPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Recurrent Orthogonal Networks and Long-Memory Tasks Mikael Henaff NYU, Facebook, Arthur , YannPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Neural Networks and Deep Learning II (Computer Vision)

    Session chair: Laurens van der Maaten

    Location:  Ballroom 3+4
  • 04:15 – Group Equivariant Convolutional Networks Taco Cohen University of Amsterdam, Max Welling University of Amsterdam / CIFARPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Learning End-to-end Video Classification with Rank-Pooling Basura Fernando ANU Canberra Australia, Stephen Gould Australian National UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Learning Physical Intuition of Block Towers by Example Adam Lerer Facebook AI Research, Sam Gross Facebook AI Research, Rob Fergus Facebook AI ResearchPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Large-Margin Softmax Loss for Convolutional Neural Networks Weiyang Liu Peking University, Yandong Wen South China University of Technology, Zhiding Yu Carnegie Mellon University, Meng Yang Shenzhen UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – Network Morphism Tao Wei University at Buffalo, Changhu Wang Microsoft Research, Yong Rui Microsoft Research, Chang Wen ChenPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Multi-Bias Non-linear Activation in Deep Neural Networks Hongyang Li The Chinese Univ. of HK, Wanli Ouyang , Xiaogang WangPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Approximate Inference

    Session chair: Jun Zhu

    Location:  Marquis
  • 04:15 – Boolean Matrix Factorization and Noisy Completion via Message Passing Siamak Ravanbakhsh CMU, Barnabas Poczos , Russell Greiner University of AlbertaPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Stochastic Discrete Clenshaw-Curtis Quadrature Nico Piatkowski TU Dortmund, Katharina Morik TU DortmundPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference Tudor Achim Stanford University, Ashish SabharwalAllen Institute for AI, Stefano ErmonPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Variable Elimination in the Fourier Domain Yexiang Xue Cornell University, Stefano Ermon , Ronan Le Bras Cornell University, Carla , BartPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – Learning and Inference via Maximum Inner Product Search Stephen Mussmann Stanford University, Stefano ErmonPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation David Wipf Microsoft Research, BeijingPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Metric and Manifold Learning / Kernel Methods

    Session chair: Le Song

    Location:  Lyceum
  • 04:15 – Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing Ke Li UC Berkeley, Jitendra MalikPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Geometric Mean Metric Learning Pourya Zadeh Tehran university, Reshad Hosseini , Suvrit SraPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Low-rank tensor completion: a Riemannian manifold preconditioning approach Hiroyuki Kasai The University of Electro-Comm, Bamdev Mishra Amazon Development Centre IndiaPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – The Variational Nystrom method for large-scale spectral problems Max Vladymyrov Yahoo Labs, Miguel Carreira-Perpinan UC MercedPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – Fast DPP Sampling for Nystro ̈m with Application to Kernel Methods Chengtao Li MIT, Stefanie Jegelka MIT, Suvrit SraPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Computationally Efficient Nystr\”{o}m Approximation using Fast Transforms Si Si , Cho-Jui Hsieh UC Davis, InderjitPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Statistical Learning Theory

    Session chair: Ohad Shamir

    Location:  Empire
  • 04:15 – Barron and Cover’s Theory in Supervised Learning and its Application to Lasso Masanori Kawakita Kyushu University, Jun’ichi Takeuchi Kyushu UniversityPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Exact Exponent in Optimal Rates for Crowdsourcing Chao Gao Yale University, Yu Lu Yale University, Dengyong Zhou Microsoft ResearchPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin Istituto Italiano di Tecnologi, Raffaello Camoriano IIT Italy and UNIGE Italy, Lorenzo Rosasco Istituto Italiano di Tecnologia, Università degli Studi di Genova and MITPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Generalized Direct Change Estimation in Ising Model Structure Farideh Fazayeli University of Minnesota, Arindam BanerjeePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – Gaussian process nonparametric tensor estimator and its minimax optimality Heishiro Kanagawa Tokyo Institute of Technology, Taiji Suzuki , Hayato Kobayashi Yahoo Japan Corporation, Nobuyuki Shimizu , Yukihiro Tagami Yahoo Japan CorporationPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Minimum Regret Search for Single- and Multi-Task Optimization Jan Hendrik Metzen University BremenPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Monday – Structured Prediction / Monte Carlo Methods

    Session chair: Martin Jaggi

    Location:  Soho
  • 04:15 – The Sum-Product Theorem: A Foundation for Learning Tractable Models Abram Friesen University of Washington, PedroPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:32 – Train and Test Tightness of LP Relaxations in Structured Prediction Ofer Meshi , Mehrdad Mahdavi , Adrian Weller University of Cambridge, David Sontag NYUPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 04:49 – Evasion and Hardening of Tree Ensemble Classifiers Alex Kantchelian University of California, Berk, J. D. Tygar UC Berkeley, Anthony Joseph UC BerkeleyPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:25 – Importance Sampling Tree for Large-scale Empirical Expectation Olivier CANEVET Idiap Research Institut, Cijo Jose Idiap Research Institute/ Éc , Francois Fleuret Idiap research institutePaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:42 – Stratified Sampling Meets Machine Learning Edo Liberty , Kevin Lang Yahoo Labs, Konstantin Shmakov Yahoo LabsPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract
  • 05:59 – Scalable Discrete Sampling as a Multi-Armed Bandit Problem Yutian Chen University of Cambridge, ZoubinPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Neural Networks and Deep Learning

    Session chair: Hal Daume III

    Location:  Ballroom 1+2+Juliard
  • 10:30 – Strongly-Typed Recurrent Neural Networks David Balduzzi , Muhammad Ghifary Victoria University Wellington, Weta DigitalPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – A Convolutional Attention Network for Extreme Summarization of Source Code Miltiadis Allamanis University of Edinburgh, UK, Hao Peng Peking University, China, Charles SuttonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Ask Me Anything: Dynamic Memory Networks for Natural Language Processing Ankit Kumar MetaMind, Ozan Irsoy MetaMind, Peter Ondruska , Mohit Iyyer MetaMind, James Bradbury MetaMind, Ishaan Gulrajani MetaMind, Victor Zhong MetaMind, Romain Paulus MetaMind, Richard SocherPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Dynamic Memory Networks for Visual and Textual Question Answering Caiming Xiong MetaMind, Stephen Merity MetaMind, Richard SocherPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings Rie Johnson RJ Research Consulting, Tong ZhangPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – PHOG: Probabilistic Model for Code Pavol Bielik ETH Zurich, Veselin Raychev ETH Zurich, Martin Vechev ETH ZurichPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Reinforcement Learning

    Session chair: Tom Erez

    Location:  Ballroom 3+4
  • 10:30 – On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search Piyush Khandelwal University of Texas at Austin, Elad Liebman , Scott , Peter Stone U. of TexasPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – Generalization and Exploration via Randomized Value Functions Ian Osband Stanford, Benjamin Van Roy Stanford University, Zheng Wen Adobe ResearchPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Doubly Robust Off-policy Value Evaluation for Reinforcement Learning Nan Jiang University of Michigan, Lihong Li MicrosoftPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Near Optimal Behavior via Approximate State Abstraction David Abel Brown University, David Hershkowitz Brown University, Michael LittmanPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Model-Free Trajectory Optimization\\ for Reinforcement Learning Riad Akrour TU Darmstadt, Gerhard Neumann , Hany Abdulsamad, Abbas AbdolmalekiPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – Model-Free Imitation Learning with Policy Optimization Jonathan Ho Stanford, Jayesh Gupta Stanford University, Stefano ErmonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    Session chair: Lihong Li

    Location:  Marquis
  • 03:40 – Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization Chelsea Finn UC Berkeley, Sergey Levine , Pieter Abbeel BerkeleyPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Smooth Imitation Learning for Online Sequence Prediction Hoang Le Caltech, Andrew Kang , Yisong Yue Caltech, Peter CarrPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Continuous Deep Q-Learning with Model-based Acceleration Shixiang Gu University of Cambridge, Timothy Lillicrap Google DeepMind, Ilya Sutskever OpenAI, Sergey Levine GooglePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Google DeepMind, Adria Puigdomenech Badia Google DeepMind, Mehdi Mirza , Alex Graves Google DeepMind, Timothy Lillicrap Google DeepMind, Tim Harley Google DeepMind, David Silver Google Deepmind, Koray Kavukcuoglu Google DeepmindPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    Session chair: Tom Erez

    Location:  Marquis
  • 05:10 – Estimating Maximum Expected Value through Gaussian Approximation Carlo D’Eramo Politecnico di Milano, Marcello RestelliPolitecnico di Milano, Alessandro Nuara Politecnico di MilanoPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning Philip Thomas CMU, EmmaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control Prashanth L.A. University of Maryland , Cheng Jie University of Maryland – College Park, Michael Fu University of Maryland – College Park, Steve Marcus University of Maryland – College Park, Csaba Szepesvari AlbertaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – Softened Approximate Policy Iteration for Markov Games Julien Pérolat Univ. Lille, Bilal Piot Univ. Lille, Matthieu Geist , Bruno Scherrer , Olivier Pietquin Univ. Lille, CRIStAL, UMR 9189, SequeL Team, Villeneuve d’Ascq, 59650, FRANCEPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Optimization (Combinatorial)

    Session chair: Andreas Krause

    Location:  Marquis
  • 10:30 – Algorithms for Optimizing the Ratio of Submodular Functions Wenruo Bai University of Washington, Rishabh Iyer , Kai Wei , Jeff Bilmes U. of WashingtonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – Horizontally Scalable Submodular Maximization Mario Lucic ETH Zurich, Olivier Bachem ETH Zurich, Morteza ZadimoghaddamGoogle Research, Andreas KrausePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization Eric Balkanski , Baharan MirzasoleimanETH Zurich, Andreas Krause , Yaron SingerPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Fast Constrained Submodular Maximization: Personalized Data Summarization Baharan Mirzasoleiman ETH Zurich, Ashwinkumar Badanidiyuru Google Research, Amin Karbasi Yale UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – A Box-Constrained Approach for Hard Permutation Problems Cong Han Lim Univ of Wisconsin – Madison, Steve Wright University of Wisconsin-MadisonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery Ian En-Hsu Yen University of Texas at Austin, Xin Lin University of Texas at Austin, Jiong Zhang University of Texas at Austin, Pradeep Ravikumar UT Austin, InderjitPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Unsupervised Learning / Representation Learning

    Session chair: Jennifer Dy

    Location:  Lyceum
  • 10:30 – Nonparametric Canonical Correlation Analysis Tomer Michaeli Technion, Weiran Wang , Karen Livescu TTI ChicagoPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – The Information Sieve Greg Ver Steeg Information Sciences Institute, Aram Galstyan Information Sciences InstitutePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Gromov-Wasserstein Averaging of Kernel and Distance Matrices Gabriel Peyré , Marco Cuturi Kyoto, Justin SolomonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Learning Representations for Counterfactual Inference Fredrik Johansson Chalmers Technical University, Uri Shalit , David SontagNYUPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Why Regularized Auto-Encoders learn Sparse Representation? Devansh Arpit SUNY Buffalo, Yingbo Zhou SUNY Buffalo, Hung NgoSUNY Buffalo, Venu Govindaraju SUNY BuffaloPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – Robust Random Cut Forest Based Anomaly Detection on Streams Sudipto Guha University of Pennsylvania, Nina Mishra , Gourav Roy Amazon, Okke Schrijvers Stanford UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Sampling / Kernel Methods

    Session chair: Marius Kloft

    Location:  Empire
  • 10:30 – Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends Christopher Tosh UC San DiegoPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – Pliable Rejection Sampling Akram Erraqabi Inria Lille Nord Europe, Michal Valko Inria Lille – Nord Europe, Alexandra Carpentier , Odalric Maillard InriaPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – A Kernel Test of Goodness of Fit Kacper.chwialkowski@ Chwialkowski Ucl, Heiko Strathmann University College London, Arthur Gretton UCL GatsbyPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – A Kernelized Stein Discrepancy for Goodness-of-fit Tests qiang liu , Jason Lee UC Berkeley, MichaelPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Additive Approximations in High Dimensional Nonparametric Regression via the SALSA Kirthevasan Kandasamy Carnegie Mellon University, Yaoliang YuPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – Doubly Decomposing Nonparametric Tensor Regression Masaaki Imaizumi University of Tokyo, Kohei Hayashi NIIPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Sparsity and Compressed Sensing

    Session chair: Gal Chechik

    Location:  Soho
  • 10:30 – The Information-Theoretic Requirements of Subspace Clustering with Missing Data Daniel Pimentel-Alarcon UW-Madison, Robert Nowak UW MadisonPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – Robust Principal Component Analysis with Side Information Kai-Yang Chiang UT Austin, Cho-Jui Hsieh UC Davis, InderjitPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit Jie Shen Rutgers University, Ping Li Rutgers, Huan XuPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow Huishuai Zhang Syracuse University, Yuejie Chi Ohio State University, Yingbin Liang Syracuse UniversityPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Estimating Structured Vector Autoregressive Models Igor Melnyk University of Minnesota, Arindam BanerjeePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation Huan Gui University of Illinois at Urba, Jiawei Hanuniversity of illinois at urbana-champaign, Quanquan GuPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Approximate Inference

    Session chair: Jon Mcauliffe

    Location:  Liberty
  • 10:30 – Hierarchical Variational Models Rajesh Ranganath , Dustin Tran Columbia University, Blei David ColumbiaPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 10:47 – A Variational Analysis of Stochastic Gradient Algorithms Stephan Mandt Columbia University, Matthew Hoffman Adobe Research, Blei David ColumbiaPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:04 – Black-Box Alpha Divergence Minimization Jose miguel Hernandez-Lobato , Yingzhen Li University of Cambridge, Mark RowlandUniversity of Cambridge, Thang Bui University of Cambridge, Daniel Hernandez-Lobato , Richard Turner University of CambridgePaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:40 – Variational Inference for Monte Carlo Objectives Andriy Mnih , Danilo Rezende Google DeepMindPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 11:57 – Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Yarin Gal University of Cambridge, ZoubinPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract
  • 12:14 – Auxiliary Deep Generative Models Lars Maaløe Technical University Denmark, Casper Kaae Sønderby University of Copenhagen, Søren Kaae Sønderby University of Copenagen, Ole Winther Technical University of DenmarkPaper | Reviews | Rebuttal | Poster session on monday afternoon 3:00pm-7:00pm | Abstract

    ⤴

    Tuesday – Neural Networks and Deep Learning I

    Session chair: Nicolas Le Roux

    Location:  Ballroom 1+2+Juliard
  • 03:40 – Factored Temporal Sigmoid Belief Networks for Sequence Learning Jiaming Song Tsinghua University, Zhe Gan Duke University, Lawrence CarinPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Bidirectional Helmholtz Machines Jorg Bornschein University of Montreal, Samira Shabanian University of Montreal, Asja Fischer , Yoshua Bengio U. of MontrealPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos University of Amsterdam, Max Welling University of Amsterdam / CIFARPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Dropout distillation Samuel Rota Bulò FBK, Lorenzo Porzi FBK, Peter Kontschieder Microsoft Research CambridgePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    Session chair: Yoshua Bengio

    Location:  Ballroom 1+2+Juliard
  • 05:10 – Expressiveness of Rectifier Networks Xingyuan Pan University of Utah, Vivek Srikumar University of UtahPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Convolutional Rectifier Networks as Generalized Tensor Decompositions Nadav Cohen Hebrew University of Jerusalem, Amnon Shashua MobileyePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Fixed Point Quantization of Deep Convolutional Networks Darryl Lin Qualcomm Research, Sachin Talathi Qualcomm Research, Sreekanth Annapureddy NetraDyne Inc.Paper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy Ran Gilad-Bachrach Microsoft Research, Nathan Dowlin Princeton, Kim Laine Microsoft Research, Kristin Lauter Microsoft Research, Michael Naehrig Microsoft Research, John Wernsing Microsoft ResearchPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Neural Networks and Deep Learning II

    Session chair: Alexandru Niculescu-Mizil

    Location:  Ballroom 3+4
  • 03:40 – Revisiting Semi-Supervised Learning with Graph Embeddings Zhilin Yang Carnegie Mellon University, William Cohen CMU, Ruslan Salakhudinov U. of TorontoPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – ADIOS: Architectures Deep In Output Space Moustapha Cisse , Maruan Al-Shedivat CMU, Samy Bengio GooglePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Unsupervised Deep Embedding for Clustering Analysis Junyuan Xie University of Washington, Ross Girshick Facebook, Ali FarhadiUniversity of WashingtonPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Learning Convolutional Neural Networks for Graphs Mathias Niepert NEC Laboratories Europe, Mohamed Ahmed NEC Laboratories Europe, Konstantin Kutzkov NEC Laboratories EuropePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    Session chair: David Sontag

    Location:  Ballroom 3+4
  • 05:10 – Correcting Forecasts with Multifactor Neural Attention Matthew Riemer IBM, Aditya Vempaty IBM, Flavio Calmon IBM, Fenno HeathIBM, Richard Hull IBM, Elham Khabiri IBMPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Meta-Learning with Memory-Augmented Neural Networks Adam Santoro Google DeepMind, Sergey Bartunov Higher School of Economics, Matthew Botvinick , Daan Wierstra Google DeepMind, Timothy Lillicrap Google DeepMindPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Learning Simple Algorithms from Examples Wojciech Zaremba , Tomas , Armand Joulin , Rob Fergus Facebook AI ResearchPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – Associative Long Short-Term Memory Ivo Danihelka Google DeepMind, Greg Wayne Google DeepMind, Benigno Uria Google DeepMind, Nal Kalchbrenner Google Deepmind, Alex Graves Google DeepMindPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Optimization (Continuous)

    Session chair: Le Song

    Location:  Lyceum
  • 03:40 – On the Statistical Limits of Convex Relaxations Zhaoran Wang Princeton University, Quanquan Gu , HanPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier Jacob Abernethy U. of Michigan, Elad HazanPrinceton UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – A ranking approach to global optimization Cedric Malherbe ENS Cachan, Emile Contal ENS Cachan, Nicolas Vayatis ENS CachanPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Epigraph projections for fast general convex programming Po-Wei Wang Carnegie Mellon University, Matt Wytock , ZicoPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    Session chair: Tong Zhang

    Location:  Lyceum
  • 05:10 – Low-rank Solutions of Linear Matrix Equations via Procrustes Flow Stephen Tu UC Berkeley, Ross Boczar UC Berkeley, Max Simchowitz UC Berkeley, mahdi Soltanolkotabi , Ben Recht BerkeleyPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods Huikang Liu CUHK, Weijie Wu CUHK, Anthony Man-Cho SoPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis Rong Ge , Chi JinUC Berkeley, Sham , Praneeth Netrapalli Microsoft Research, Aaron Sidford Microsoft Research, New EnglandPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization Zhiqiang Xu Institute of Infocomm Research, Peilin Zhao I2R, ASTAR, Jianneng Cao , Xiaoli LiPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Matrix Factorization and Related Topics

    Session chair: Roger Grosse

    Location:  Empire
  • 03:40 – Principal Component Projection Without Principal Component Analysis Roy Frostig Stanford University, Cameron MuscoMassachusetts Institute of Technology, Christopher Musco Mass. Institute of Technology, Aaron Sidford Microsoft Research, New EnglandPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Recovery guarantee of weighted low-rank approximation via alternating minimization Yuanzhi Li Princeton University, Yingyu LiangPrinceton, Andrej Risteski Princeton UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Tensor Decomposition via Joint Matrix Schur Decomposition Nicolo Colombo Univ of Luxembourg, Nikos Vlassis AdobePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Fast methods for estimating the Numerical rank of large matrices Shashanka Ubaru University of Minnesota, Yousef Saad University of MinnesotaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Unsupervised Learning / Applications

    Session chair: Jeff Bilmes

    Location:  Soho
  • 03:40 – Markov-modulated Marked Poisson Processes for Check-in Data Jiangwei Pan Duke University, Vinayak Rao Purdue University, Pankaj Agarwal Duke Univeristy, Alan Gelfand Duke UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Hierarchical Compound Poisson Factorization Mehmet Basbug Princeton University, Barbara EngelhardtPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data Sandhya PrabhakaranColumbia University, Elham Azizi Columbia University, Ambrose Carr Columbia University, Dana Pe’er Columbia UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series Yunseong Hwang UNIST, Anh Tong UNIST, Jaesik Choi UNISTPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Learning Theory

    Session chair: Jon Mcauliffe

    Location:  Liberty
  • 03:40 – Truthful Univariate Estimators Ioannis Caragiannis University of Patras, Ariel Procaccia Carnegie Mellon University, Nisarg ShahCarnegie Mellon UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Fast Algorithms for Segmented Regression Jayadev Acharya MIT, Ilias Diakonikolas , Jerry Li MIT, Ludwig SchmidtPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues Nihar Shah UC Berkeley, Sivaraman Balakrishnan CMU, Aditya Guntuboyina UC Berkeley, Martin Wainwright UC BerkeleyPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:31 – Provable Algorithms for Inference in Topic Models Sanjeev Arora Princeton University, Rong Ge , Frederic Koehler Princeton University, Tengyu Ma Princeton University, Ankur MoitraPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Large Scale Learning and Big Data

    Session chair: Andreas Krause

    Location:  Empire
  • 05:10 – Extreme F-measure Maximization using Sparse Probability Estimates Kalina Jasinska , Krzysztof Dembczynski , Robert Busa-Fekete , Karlson Pfannschmidt , Timo Klerx , Eyke HullermeierPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Stochastic Optimization for Multiview Representation Learning using Partial Least Squares Raman Arora Johns Hopkins University, Poorya Mianjy Johns Hopkins University, Teodor MarinovPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Gaussian quadrature for matrix inverse forms with applications Chengtao Li MIT, Suvrit Sra , Stefanie Jegelka MITPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling Mostafa Rahmani University of Central Florida, Geroge Atia University of Central FloridaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Graphical Models

    Session chair: Jun Zhu

    Location:  Soho
  • 05:10 – Uprooting and Rerooting Graphical Models Adrian Weller University of CambridgePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Structure Learning of Partitioned Markov Networks Song Liu The Inst. of Stats. Math., Taiji Suzuki , Masashi Sugiyama University of Tokyo, Kenji Fukumizu The Institute of Statistical MathematicsPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • Best paper award – 05:44 – Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling Christopher De Sa Stanford, Chris ReStanford University, Kunle Olukotun StanfordPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – Estimation from Indirect Supervision with Linear Moments Aditi Raghunathan Stanford University, Roy Frostig Stanford University, John , Percy Liang StanfordPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Tuesday – Supervised Learning

    Session chair: Nicolas Le Roux

    Location:  Liberty
  • 05:10 – Early and Reliable Event Detection Using Proximity Space Representation Maxime Sangnier LTCI, CNRS, Télécom ParisTech, Jerome Gauthier CEA, Alain RakotomamonjyPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:27 – Meta–Gradient Boosted Decision Tree Model for Weight and Target Learning Yury Ustinovskiy Yandex, Valentina FedorovaYandex, Gleb Gusev Yandex, Pavel Serdyukov YandexPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 05:44 – Differential Geometric Regularization for Supervised Learning of Classifiers Qinxun Bai Boston University, Steven RosenbergBoston University, Zheng Wu The Mathwork Inc., Stan Sclaroff Boston UniversityPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 06:01 – Linking losses for density ratio and class-probability estimation Aditya Menon National ICT Australia, Cheng Soon Ong NICTAPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Neural Networks and Deep Learning I

    Session chair: Samy Bengio

    Location:  Ballroom 1+2+Juliard
  • 08:30 – Neural Variational Inference for Text Processing Yishu Miao University of Oxford, Lei Yu University of Oxford, Phil BlunsomPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – A Deep Learning Approach to Unsupervised Ensemble Learning Uri Shaham Yale University, Xiuyuan Cheng , Omer Dror , Ariel Jaffe , Boaz Nadler , Joseph Chang , Yuval KlugerPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification Andre Martins , Ramon Astudillo UnbabelPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – A Neural Autoregressive Approach to Collaborative Filtering Yin Zheng Hulu LLC., Bangsheng Tang Hulu LLC, Wenkui Ding Hulu LLC., Hanning Zhou HuluPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters Jelena Luketina Aalto University, Tapani Raiko , Mathias Berglund Aalto University, Klaus Greff IDSIAPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Optimization (Continuous)

    Session chair: Shie Mannor

    Location:  Ballroom 3+4
  • 08:30 – SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu University of Hong Kong, Peter Richtarik , Martin Takac , Olivier Fercoq LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, 75013, Paris, FrancePaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – Stochastic Block BFGS: Squeezing More Curvature out of Data Robert Gower University of Edinburgh, Donald Goldfarb Columbia University, Peter RichtarikPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification Ian En-Hsu Yen University of Texas at Austin, Xiangru Huang UTaustin, Pradeep Ravikumar UT Austin, Kai Zhong ICES department, University of Texas at Austin, InderjitPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms Yu-Xiang Wang , Veeranjaneyulu Sadhanala , Wei Dai Carnegie Mellon University, Willie Neiswanger , Suvrit Sra , Eric Xing CMUPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs Anton Osokin , Jean-Baptiste Alayrac ENS, Isabella Lukasewitz INRIA, Puneet Dokania INRIA and Ecole Centrale Paris, Simon Lacoste-Julien INRIAPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    Session chair: Satyen Kale

    Location:  Ballroom 3+4
  • 10:20 – On the Iteration Complexity of Oblivious First-Order Optimization Algorithms Yossi Arjevani Weizmann Institute of Science, Ohad Shamir Weizmann Institute of SciencePaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – Variance-Reduced and Projection-Free Stochastic Optimization Elad Hazan Princeton University, Haipeng LuoPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – On Graduated Optimization for Stochastic Non-Convex Problems Elad Hazan Princeton University, Kfir Yehuda Levy Technion, Shai Shalev-Shwartz Hebrew University of JerusalemPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization Frank Curtis Lehigh UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums Anton Rodomanov Higher School of Economics, Dmitry Kropotov Moscow State UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning Xingguo Li University of Minnesota, Tuo Zhao , Raman Arora Johns Hopkins University, Han , Jarvis HauptPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 03:40 – Energetic Natural Gradient Descent Philip Thomas CMU, Bruno Castro da Silva , Christoph Dann Carnegie Mellon University, EmmaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – On the Quality of the Initial Basin in Overspecified Neural Networks Itay Safran Weizmann Institute of Science, Ohad ShamirWeizmann Institute of SciencePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – L1-regularized Neural Networks are Improperly Learnable in Polynomial Time Yuchen Zhang , Jason , MichaelPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Multi-label, multi-task, and neural networks

    Session chair: Joelle Pineau

    Location:  Marquis
  • 08:30 – Asymmetric Multi-task Learning based on Task Relatedness and Confidence Giwoong Lee UNIST, Eunho Yang IBM Research, Sung ju Hwang UNISTPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – Training Deep Neural Networks via Direct Loss Minimization Yang Song Tsinghua University, Alexander Schwing , Richard , Raquel Urtasun U. of TorontoPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – Structured Prediction Energy Networks David Belanger University of Massachusetts Am, Andrew McCallumPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Conditional Bernoulli Mixtures for Multi-label Classification Cheng Li Northeastern University, Bingyu Wang Northeastern University, Virgil Pavlu Northeastern University, Javed Aslam Northeastern UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Training Neural Networks Without Gradients: A Scalable ADMM Approach Gavin Taylor US Naval Academy, Ryan Burmeister US Naval Academy, Zheng Xu University of Maryland, Bharat Singh University of Maryland, Colleg, Ankit Patel Rice University, Tom GoldsteinUniversity of MarylandPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Gaussian Processes

    Session chair: Roger Grosse

    Location:  Lyceum
  • 08:30 – Stability of Controllers for Gaussian Process Forward Models Julia Vinogradska Robert Bosch GmBH, Bastian Bischoff , Duy Nguyen-Tuong , Anne Romer , Henner Schmidt , Jan PetersPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models Trong Nghia Hoang NUS, Quang Minh Hoang NUS, Bryan Kian Hsiang Low NUSPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – Deep Gaussian Processes for Regression using Approximate Expectation Propagation Thang Bui University of Cambridge, Daniel Hernandez-Lobato , Jose miguel Hernandez-Lobato , Yingzhen Li University of Cambridge, Richard Turner University of CambridgePaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Preconditioning Kernel Matrices Kurt Cutajar EURECOM, Michael Osborne , John Cunningham Columbia University, Maurizio Filippone EURECOMPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Extended and Unscented Kitchen Sinks Edwin Bonilla UNSW, Daniel Steinberg DATA61, Alistair Reid Data61Paper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Feature Selection and Dimensionality Reduction

    Session chair: Laurens van der Maaten

    Location:  Empire
  • 08:30 – On the Consistency of Feature Selection With Lasso for Non-linear Targets Yue Zhang Case Western Reserve University, Weihong Guo Case Western Reserve University, Soumya RayPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – No penalty no tears: Least squares in high-dimensional linear models Xiangyu Wang Duke University, David , Chenlei LengUniversity of WarwickPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling Atsushi Shibagaki Nagoya Institute of Technology, Masayuki Karasuyama Nagoya Institute of Technology, Kohei Hatano Kyushu University, Ichiro TakeuchiPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity Quanming Yao HKUST, James KwokHong Kong University Science TechnologyPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – How to Fake Multiply by a Gaussian Matrix Michael Kapralov , Vamsi Potluru Comcast Cable, David WoodruffPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Graph Analysis/ Spectral Methods

    Session chair: Alex Kulesza

    Location:  Soho
  • 08:30 – Metadata-conscious anonymous messaging Giulia Fanti UIUC, Peter Kairouz UIUC, Sewoong Oh UIUC, Kannan Ramchandran UC Berkeley, Pramod Viswanath UIUCPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – A Simple and Strongly-Local Flow-Based Method for Cut Improvement Nate Veldt Purdue Unversity, David Gleich Purdue University, MichaelPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – Community Recovery in Graphs with Locality Yuxin Chen Stanford University, Govinda Kamath Stanford University, Changho SuhKAIST, David Tse Stanford UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Interactive Bayesian Hierarchical Clustering Sharad Vikram UCSD, Sanjoy Dasgupta UCSDPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Cross-Graph Learning of Multi-Relational Associations Hanxiao Liu Carnegie Mellon University, Yiming YangPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Ranking and Preference Learning

    Session chair: Tong Zhang

    Location:  Liberty
  • 08:30 – Controlling the distance to a Kemeny consensus without computing it Anna Korba Telecom Paris Tech, Yunlong Jiao Mines Paris Tech, Eric Sibony Telecom Paris TechPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 08:47 – Data-driven Rank Breaking for Efficient Rank Aggregation Ashish Khetan UIUC, Sewoong Oh UIUCPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:04 – Parameter Estimation for Generalized Thurstone Choice Models Milan Vojnovic Microsoft, Seyoung Yun MicrosoftPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:21 – Learning Mixtures of Plackett-Luce Models Zhibing Zhao RPI, Peter Piech RPI, Lirong Xia RPIPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 09:38 – Recommendations as Treatments: Debiasing Learning and Evaluation Tobias Schnabel Cornell University, Adith SwaminathanCornell University, Ashudeep Singh Cornell University, Navin Chandak Google, Thorsten Joachims CornellPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Neural Networks and Deep Learning

    Session chair: Yoshua Bengio

    Location:  Ballroom 1+2+Juliard
  • 10:20 – Generative Adversarial Text to Image Synthesis Scott Reed , Zeynep Akata Max Planck Institute for Informatics, Xinchen YanUniversity of Michigan, Lajanugen Logeswaran University of Michigan – Ann Arbor, Bernt Schiele , Honglak Lee University of MichiganPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – Autoencoding beyond pixels using a learned similarity metric Anders Boesen Lindbo Larsen Technical University of Denmar, Søren Kaae Sønderby University of Copenagen, Hugo Larochelle Twitter, Ole Winther Technical University of DenmarkPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – Exploiting Cyclic Symmetry in Convolutional Neural Networks Sander Dieleman Google DeepMind, Jeffrey De Fauw Google DeepMind, Koray Kavukcuoglu Google DeepmindPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – A Comparative Analysis and Study of Multiview CNN Models for Joint Object Categorization and Pose Estimation Mohamed Elhoseiny Rutgers University, Tarek El-Gaaly Rutgers University, Amr Bakry Rutgers University, Ahmed Elgammal Rutgers UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – Dynamic Capacity Networks Amjad Almahairi , Nicolas Ballas , Tim Cooijmans University of Montreal, Yin Zheng Hulu LLC., Hugo Larochelle Twitter, Aaron CourvillePaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification Yuting ZhangUniversity of Michigan, Kibok Lee University of Michigan, Honglak Lee University of MichiganPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Applications and Time-Series Analysis

    Session chair: Jon Mcauliffe

    Location:  Marquis
  • 10:20 – Hierarchical Decision Making In Electricity Grid Management Gal Dalal Technion, Elad Gilboa Technion, Shie Mannor TechnionPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission Jinsung YoonUniversity of California, Los , Ahmed Alaa University of California, Los Angeles, Scott Hu University of California, Los Angeles, Mihaela van der SchaarPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – Power of Ordered Hypothesis Testing Lihua Lei Lihua, William Fithian UC Berkeley, Department of StatisticsPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – Learning to Filter with Predictive State Inference Machines Wen Sun Carnegie Mellon University, Arun Venkatraman Carnegie Mellon University, Byron Boots , J.Andrew Bagnell Carnegie Mellon UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – Learning Population-Level Diffusions with Generative RNNs Tatsunori Hashimoto MIT, David Gifford MIT, Tommi Jaakkola MITPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching Mu Niu University of Glasgow, Simon Rogers University of Glasgow, Maurizio Filippone EURECOM, Dirk Husmeier University of GlasgowPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Dimensionality Reduction / Private Learning

    Session chair: Jeff Bilmes

    Location:  Lyceum
  • 10:20 – Greedy Column Subset Selection: New Bounds and Distributed Algorithms Jason Altschuler Princeton University, Aditya Bhaskara, Gang Fu Google Research, Vahab Mirrokni Google Research, Afshin Rostamizadeh Google, Morteza Zadimoghaddam Google ResearchPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – Efficient Private Empirical Risk Minimization for High-dimensional Learning Shiva Prasad Kasiviswanathan Samsung Research America, Hongxia Jin Samsung Research AmericaPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – Binary embeddings with structured hashed projections Anna Choromanska Courant Institute, NYU, Krzysztof Choromanski Google Research NYC, Mariusz Bojarski NVIDIA, Tony Jebara Columbia, Sanjiv Kumar , YannPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – Differentially Private Policy Evaluation Borja Balle Lancaster University, Maziar Gomrokchi McGill University, Doina Precup McGillPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – Learning from Multiway Data: Simple and Efficient Tensor Regression Rose Yu University of Southern Cal, Yan LiuPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Low-Rank Matrix Approximation with Stability Dongsheng Li IBM Research – China, Chao Chen , Qin Lv , Junchi Yan , Li Shang , Stephen ChuPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Monte Carlo Methods

    Session chair: Stefano Ermon

    Location:  Empire
  • 10:20 – Interacting Particle Markov Chain Monte Carlo Tom Rainforth University of Oxford, Christian Naesseth Linköping University, Fredrik Lindsten Uppsala University, Brooks Paige University of Oxford, Jan-Willem Vandemeent , Arnaud Doucet University of Oxford, Frank WoodPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – Slice Sampling on Hamiltonian Trajectories Benjamin Bloem-Reddy Columbia University, John Cunningham Columbia UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – Robust Monte Carlo Sampling using Riemannian Nos\'{e}-Poincar\'{e} Hamiltonian Dynamics Anirban Roychowdhury , Brian KulisBoston University, Srinivasan ParthasarathyPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – Inference Networks for Sequential Monte Carlo in Graphical Models Brooks Paige University of Oxford, Frank WoodPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – Partition Functions from Rao-Blackwellized Tempered Sampling David Carlson Columbia University, Patrick Stinson Columbia University, Ari Pakman Columbia University, LiamPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Stochastic Quasi-Newton Langevin Monte Carlo Umut Simsekli Telecom ParisTech, Roland Badeau , Taylan Cemgil , Gaël RichardPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Crowdsourcing and Interactive Learning

    Session chair: Yisong Yue

    Location:  Soho
  • 10:20 – No Oops, You Won’t Do It Again: Mechanisms for Self-correction in Crowdsourcing Nihar Shah UC Berkeley, Dengyong ZhouMicrosoft ResearchPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – The Label Complexity of Mixed-Initiative Classifier Training Jina Suh Microsoft, Xiaojin Zhu University of Wisconsin, Saleema Amershi MicrosoftPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks Yingfei Wang Princeton University, Chu Wang , Warren PowellPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – Estimating Accuracy from Unlabeled Data: A Bayesian Approach Emmanouil Antonios Platanios Carnegie Mellon University, Avinava Dubey Carnegie Mellon University, Tom Mitchell Carnegie Mellon UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – Actively Learning Hemimetrics with Applications to Eliciting User Preferences Adish Singla , Sebastian Tschiatschek ETH Zurich, Andreas KrausePaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Optimality of Belief Propagation for Crowdsourced Classification Jungseul Ok KAIST, Sewoong Oh UIUC, Jinwoo Shin KAIST, Yung Yi KAISTPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract

    ⤴

    Wednesday – Learning Theory

    Session chair: Alina Beygelzimer

    Location:  Liberty
  • 10:20 – Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives Zeyuan Allen-Zhu Princeton University, Yang YuanCornellPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:37 – Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Princeton University, Elad Hazan Princeton UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 10:54 – Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Princeton University, Zheng Qu The University of Hong Kong, Peter Richtarik , Yang Yuan CornellPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:30 – False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking QianQian Xu IIE, CAS, Jiechao Xiong Peking University, Xiaochun Cao Institute of information engineering, CAS, Yuan Yao Peking UniversityPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 11:47 – On the Power and Limits of Distance-Based Learning Periklis Papakonstantinou Rutgers University , Jia Xu Chinese Academy of Sciences, Guang Yang ICT, BeijingPaper | Reviews | Rebuttal | Poster session on tuesday afternoon 3pm-7pm | Abstract
  • 12:04 – Train faster, generalize better: Stability of stochastic gradient descent Moritz Hardt Google, Ben Recht Berkeley, YoramPaper | Reviews | Rebuttal | Poster session on tuesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Supervised Learning

    Session chair: Csaba Szepesvari

    Location:  Ballroom 3+4
  • 03:40 – Sparse Nonlinear Regression: Parameter Estimation Zhuoran Yang Princeton University, Zhaoran Wang Princeton University, Han , Yonina Eldar Technion, Tong ZhangPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms Mathieu Blondel NTT, Masakazu Ishihata NTT Communication Science Labo, Akinori Fujino NTT, Naonori UedaPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Hyperparameter optimization with approximate gradient Fabian Pedregosa INRIAPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Kernel Methods

    Session chair: Marius Kloft

    Location:  Marquis
  • 03:40 – DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression Jovana Mitrovic University of Oxford, Dino Sejdinovic University of Oxford, Yee-Whye Teh OxfordPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Persistence weighted Gaussian kernel for topological data analysis Genki Kusano Tohoku University, Yasuaki Hiraoka , Kenji Fukumizu The Institute of Statistical MathematicsPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Discriminative Embeddings of Latent Variable Models for Structured Data Hanjun Dai Georgia Tech, Bo Dai Georgia Tech, Le SongGatechPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Matrix Factorization and Related Topics

    Session chair: Stefanie Jegelka

    Location:  Lyceum
  • 03:40 – Recycling Randomness with Structure for Sublinear time Kernel Expansions Krzysztof Choromanski Google Research NYC, Vikas Sindhwani Google ResearchPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Optimal Classification with Multivariate Losses Nagarajan Natarajan Microsoft Research India, Oluwasanmi Koyejo Stanford University & University of Illinois at Urbana Champaign, Pradeep Ravikumar UT Austin, InderjitPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Sparse Parameter Recovery from Aggregated Data Avradeep Bhowmik University of Texas at Austin, Joydeep , Oluwasanmi KoyejoStanford University & University of Illinois at Urbana ChampaignPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Privacy, Anonymity, and Security

    Session chair: Gal Chechik

    Location:  Empire
  • 03:40 – Learning privately from multiparty data Jihun Hamm , Yingjun Cao UC-San Diego, Mikhail BelkinPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing Ryan Rogers University of Pennsylvania, Salil Vadhan Harvard University, Hyun Lim UCLA, Marco Gaboardi University at BuffaloPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Discrete Distribution Estimation under Local Privacy Peter Kairouz UIUC, Keith Bonawitz Google, Daniel RamagePaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Causal Inference

    Session chair: David Sontag

    Location:  Soho
  • 03:40 – The Arrow of Time in Multivariate Time Series Stefan Bauer ETH Zurich, Bernhard Schölkopf , JonasPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications Weihao Gao UIUC, Sreeram Kannan UW Seattle, Sewoong Oh UIUC, Pramod Viswanath UIUCPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Learning Granger Causality for Hawkes Processes Hongteng Xu Georgia Tech, Mehrdad Farajtabar , HongyuanPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

    ⤴

    Wednesday – Optimization

    Session chair: Lihong Li

    Location:  Liberty
  • 03:40 – Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions Igor Colin , Aurelien Bellet INRIA, Joseph Salmon , Stéphan ClémençonPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 03:57 – Adaptive Sampling for SGD by Exploiting Side Information Siddharth GopalPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract
  • 04:14 – Mixture Proportion Estimation via Kernel Embeddings of Distributions Harish Ramaswamy , Clayton , AmbujPaper | Reviews | Rebuttal | Poster session on wednesday morning 10am-1pm | Abstract

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