Reading Group

Reading Group

20 January 2006

A. Corduneanu and C.M. Bishop, Variational Bayesian Model Selection for Mixture Distributions

Presenter: Shihao Ji, Presentation

27 January 2006

M. Kuss and C. Rassmussen, Assessing Approximations for Gaussian Process Classification

Presenter: David Williams, Presentation

3 February 2006

A. Niculescu-Mizil and R. Caruana, Learning the Structure of Related Tasks

Presenter: Lihan He, Presentation

17 February 2006

Y.W. The, M.I. Jordan, M.J. Beal and D.M. Blei, Sharing Clusters Among Related Groups: Hierarchical Dirichlet Process

Presenter: Kai Ni, Presentation

24 February 2006

E. Bart and S. Ullman, Cross-Generalization: Learning Novel Classes From A Single Example By Feature Replacement

Presenter: Nilanjan Dasgupta, Presentation

3 March 2006

H. Ishwaran and L.F. James, Gibbs Sampling Methods for Stick-Breaking Priors

Presenter: Yuting Qi, Presentation

10 March 2006

T.L. Griffiths and Z. Ghahramani, Infinite Latent Feature Models and the Indian Buffet Process

Presenter: Ya Xue, Presentation

17 March 2006

E. Meeds and S. Osindero, Bayes Sets

Presenter: Qi An, Presentation

23 March 2006

Y. Wang and Q. Ji, A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences

Presenter: Qiuhua Liu, Presentation

31 March 2006

N. Mehta, S. Natarajan, P. Tadepalli and A. Fern, Transfer in Variable-reward Hierarchical Reinforcement Learning

Presenter: Hui Li, Presentation

7 April 2006

J. Zhang, Z. Ghahramani, Y. Yang, Learning Multiple Related Tasks using Latent Independent Component Analysis

Presenter: Iulian Pruteanu, Presentation

14 April 2006

O.L. Mangasarian and E.W. Wild, Multisurface Proximal SVM Classification via Generalized Eigenvalues

Presenter: Jun Fang, Presentation

21 April 2006

A. Eliazar and R. Parr, DP-SLAM: Fast, Robust Simultaneous Localization and Mapping without Predetermined Landmarks

A. Eliazar and R. Parr, DP-SLAM 2.0

A. Eliazar and R. Parr, Constant/Linear Time Simultaneous Localization and Mapping for Dense Maps

Presenter: Lihan He, Presentation

28 April 2006

D.B. Dunson and N. Pillai, Bayesian Density Regression

Presenter: Ya Xue, Presentation

5 May 2006

R.R. Coifman et al., Geometric Diffusions as a Tool for Harmonic Analysis and Structure Definition of Data: Diffusion Maps

Presenter: Xuejun Liao, Presentation

12 May 2006

R.R. Coifman et al., Geometric Diffusions as a Tool for Harmonic Analysis and Structure Definition of Data: Multiscale Methods

Presenter: Shihao Ji, Presentation

19 May 2006

E. Sudderth, A. Torralba, W. Freeman and A. Willsky, Describing Visual Scenes Using Transformed Dirichlet Processes

Presenter: Kai Ni, Presentation

26 May 2006

S. Mahadevan and M. Maggioni, Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions

Presenter: Qi An, Presentation

2 June 2006

B. Nadler, S. Lafon, R. Coifman, I. Kevrekidis, Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators

Presenter: Nilanjan Dasgupta, Presentation

19 June 2006

M. Szummer and T. Jaakkola, Partially Labeled Classification with Markov Random Walks

Presenter: Xuejun Liao, Presentation

7 July 2006

B. Wolfe, M.R. James and S. Singh, Learning Predictive State Representations

Presenter: Hui Li, Presentation

14 July 2006

D. Justice and A. Hero, A Binary Linear Programming Formulation of the Graph Edit Distance

Presenter: Shihao Ji, Presentation

21 July 2006

X.L. Nguyen, M.J. Wainwright, M.I. Jordan, On Optimal Quantization Rules for Sequential Decision Problems

Presenter: Qi An, Presentation

28 July 2006

L. Fei-Fei and P. Perona, A Bayesian Hierarchical Model for Learning Natural Scene Categories

D. Blei and J.D. Lafferty, Dynamic Topic Models

Presenter: Iulian Pruteanu, Presentation

4 August 2006

D. Blei, J. Lafferty, Correlated Topic Models

Presenter: Chunping Wang, Presentation

25 August 2006

E.P. Xing, K.-A. Sohn, M.I. Jordan and Y.-W. Teh, Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture

Presenter: Kai Ni, Presentation

4 September 2006

D. Hähnel, D. Fox, W. Burgard, and S. Thrun, A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements

G. Grisetti, C. Stachniss, and W. Burgard, Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling

Presenter: Lihan He, Presentation

11 September 2006

J. Langford and B. Zadrozny, Reducing T-step Reinforcement Learning to Classification

D. Blatt and A. O. Hero, From weighted classification to policy search

Presenter: Hui Li, Presentation

22 September 2006

A. Hyvarinen and P. Hoyer, Emergence of Phase- and Shift-Invariant Features by decomposition of Natural Images into Independent feature Subspaces

A. Hyvarinen, P.O. Hoyer and M. Inki, Topographic Independent Component Analysis

Presenter: Iulian Pruteanu, Presentation

29 September 2006

S. Lafton and A.B. Lee, Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameterization

Presenter: Shihao Ji, Presentation

6 October 2006

O. Papaspiliopoulos and G.O. Roberts, Retrospective MCMC Methods for DP Hierarchical Models

Presenter: Yuting Qi, Presentation

13 October 2006

O. Papaspiliopoulos and G.O. Roberts, Retrospective MCMC Methods for DP Hierarchical Models and comparison of MCMC samplers for Dirichlet processors

Presenter: Yuting Qi, Presentation

20 October 2006

Graphical techniques for semi-supervised learning

Presenter: Xuejun Liao, Presentation

27 October 2006

F. Wood, T.L. Griffiths and Z. Ghahramani, A Non-Parametric Bayesian Method of Inferring Hidden Causes

Presenter: Qi An, Presentation

3 November 2006

S. Lafton, Y. Keller and R.R. Coiffman, Data Fusion and Multi-Cue Data Matching by Diffusion Maps

Presenter: Chunping Wang, Presentation

10 November 2006

A. Rodriguez, D.B. Dunson and A.E. Gelfand, The Nested Dirichlet Process

Presenter: Kai Ni, Presentation

17 November 2006

A.E. Raftery and S. Lewis, How Many Iterations in the Gibbs Sampler

Presenter: Iulian Pruteanu, Presentation

5 December 2006

M.K. Cowles and B.P. Carlin, MCMC Convergence Diagnostics: A Comparative Review

Presenter: Yuting Qi, Presentation

12 January 2007

T. Smith and R. Simmons, Heuristic Search Value Iteration for POMDPs

Presenter: Hui Li, Presentation

19 January 2007

D.B. Dunson and J.-H. Park, Kernel Stick-Breaking Processes

Presenter: Qi An, Presentation

26 January 2007

D.B. Dunson, Bayesian Dynamic Modeling of Latent Trait Distributions

Presenter: Kai Ni, Presentation

2 February 2007

N. Tatti, Distances Between Data Sets Based on Summary Statistics

Presenter: Yuting Qi, Presentation

9 February 2007

E.J. Candes, J. Romberg, T. Tao, Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information

E. Candes and J. Romberg, Practical Signal Recovery from Random Projections

Presenter: Dehong Liu, Presentation

16 February 2007

S. Kim and P. Smyth, Segmental Hidden Markov Models with Random Effects for Waveform Modeling

Presenter: Lu Ren, Presentation

23 February 2007

E.P. Xing and K.-A. Sohn, A New Nonparametric Bayesian Model for Genetic Recombination in Open Ancestral Space

Presenter: Chunping Wang, Presentation

9 March 2007

K. Watanabe and Sumio Watanabe, Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation

Presenter: Iulian Pruteanu, Presentation

16 March 2007

T. De Bie and N. Cristianini, Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems

Presenter: Lihan He, Presentation

23 March 2007

D. Zhou, O. Bousquet, T. Navin Lal, J. Weston and B. Scholkopf, Learning with Local and Global Consistency

Presenter: Qiuhua Liu, Presentation

30 March 2007

P. K. Shivaswamy, C. Bhattacharyya and A.J. Smola, Second Order Cone Programming Approaches for Handling Missing and Uncertain Data

Presenter: Qi An, Presentation

6 April 2007

H. Raghavan, O. Madani and R. Jones, Active Learning with Feedback on Both Features and Instances

Presenter: John Paisley, Presentation

27 April 2007

F. Dominici, G. Parmigiani, K.H. Reckhow and R.L. Wolpert, Combining Information from Related Regressions

Presenter: Kai Ni, Presentation

4 May 2007

F.R. Bach and M.I. Jordan, Learning Spectral Clustering, With Application to Speech Processing

Presenter: Yuting Qi, Presentation

11 May 2007

E. Evan-Dar, S. Mannor and Y. Mansour, Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems

Presenter: Shihao Ji, Presentation

18 May 2007

F.R. Bach, D. Heckerman, E. Horvitz, Considering Cost Asymmetry in Learning Classifiers

Presenter: Chunping Wang, Presentation

30 May 2007

R. Munos, Policy Gradient in Continuous Time

Presenter: Hui Li, Presentation

8 June 2007

D. Tao1, X. Li, X. Wu and S.J. Maybank, General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

Presenter: Iulian Pruteanu, Presentation

15 June 2007

R. Thibaux and M.I. Jordan, Hierarchical Beta Processes and the Indian Buffet Process

Presenter: Qi An, Presentation

9 July 2007

T. Liu, A.W. Moore and A. Gray, New Algorithms for Efficient High-Dimensional Nonparametric Classification

Presenter: Yuting Qi, Presentation

18 July 2007

S. Whiteson and P. Stone, Evolutionary Function Approximation for Reinforcement Learning

Presenter: Xuejun Liao, Presentation

27 July 2007

Y.W. Teh, D. Gorur, Z. Ghahramani, Stick-breaking construction for the Indian buffet process

Presenter: Kai Ni, Presentation

6 August 2007

A.D. Szlam, M. Maggioni and R.R. Coifman, Regularization on Graphs with Function-Adapted Diffusion Process

Presenter: Eric Wang, Presentation

15 August 2007

H. Ishwaran and M. Zarepour, Dirichlet Prior Sieves in Finite Normal Mixtures

Presenter: John Paisley, Presentation

31 August 2007

K. Kurihara, M. Welling and Y.W. Teh, Collapsed Variational Dirichlet Process Mixture Models

Presenter: Qi An, Presentation

7 September 2007

J. Hoey and J.J. Little, A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation

Presenter: Iulian Pruteanu, Presentation

14 September 2007

S. Yu, V. Tresp and K. Yu, Robust Multi-Task Learning with t-Processes

Presenter: Ivo Shterev, Presentation

21 September 2007

P. Quelhas, F. Monay, J.M. Odobez, D. Gatica-Perez and T. Tuytelaars, A Thousand Words in a Scene

Presenter: Yuting Qi, Presentation

5 October 2007

P. Domingos and M. Pazzani, On the Optimality of the Simple Bayesian Classifier under Zero-One Loss

Presenter: Lu Ren, Presentation

18 October 2007

Q. Wu, J. Guinney, M. Maggioni and S. Mukherjee, Learning Gradients: Predictive Models that Infer Geometry and Dependence

Presenter: Xuejun Liao, Presentation

26 October 2007

R.M. Neal, Density Modeling and Clustering Using Dirichlet Diffusion Trees

Presenter: Ivo Shterev, Presentation

2 November 2007

J. Guinney, Q. Wu and S. Mukherjee, Estimating Variable Structure and Dependence in Multi-Task Learning via Gradients

Presenter: John Paisley, Presentation

16 November 2007

M. Belkin and P. Niyogi, Using Manifold Structure for Partially Labelled Classification

Presenter: Chunping Wang, Presentation

30 November 2007

R. Castelo and A. Roverato, A Robust Procedure For Gaussian Graphical Model Search From Microarray DataWith p Larger Than n

Presenter: Kuan-Ming Lin, Presentation

7 December 2007

Y.W. The, K. Kurihara and M. Welling, Collapsed Variational Inference for HDP

Presenter: Iulian Pruteanu, Presentation

18 January 2007

H. Ishwaran and M. Zarepour, Exact and Approximate Sum Representations for the Dirichlet Process

Presenter: John Paisley, Presentation

25 January 2007

A.B. Owen, Infinitely Imbalanced Logistic Regression

Presenter: Ivo Shterev, Presentation

15 February 2008

J.-H. Park and D. Dunson, Bayesian Generalized Product Partition Model

Presenter: Eric Wang, Presentation

22 February 2008

R.F. MacLehose and D.B. Dunson, Bayesian semi-parametric multiple shrinkage

Presenter: Lu Ren, Presentation

3 March 2008

W. Li, D. Blei and A. McCallum, Nonparametric Bayes Pachinko Allocation

Presenter: Lihan He, Presentation

12 March 2008

N. Bouguila and D. Ziou, High-Dimensional Unsupervised Selection & Estimation of a Finite Generalized Dirichlet Mixture Model Based on MML

Presenter: Qi An, Presentation

21 March 2008

S. Ray and B. Mallik, Functional Clustering by Bayesian Wavelet Methods

Presenter: Iulian Pruteanu, Presentation

4 April 2008

M. West, Bayesian Factor Regression Models in the “Large p, Small n” Paradigm

Presenter: John Paisley, Presentation

11 April 2008

M. Dundar, B. Krishnapuram, J. Bi and R. Rao, Learning Classifiers When the Training Data Are Not IID

Presenter: Ivo Shterev, Presentation

18 April 2008

Y. Sun, M. Kamel and Y. Wang, Boosting for Learning Multiple Classes with Imbalanced Class Distribution

Presenter: Minhua Chen, Presentation

25 April 2008

H.M. Wallach, Topic Modeling: Beyond Bag of Words

Presenter: Eric Wang, Presentation

2 May 2008

J. Baxter, A Model of Inductive Bias Learning

S. Ben David and R.S. Borbely, A Notion of Task Relatedness Yielding Provable Multiple-task Learning Guarantees

Presenter: Xuejun Liao, Presentation

9 May 2008

J. Canny and T. Rattenbury, A Dynamic Topic Model for Document Segmentation

Presenter: Lan Du, Presentation

16 May 2008

S.M. O’Brien and D. Dunson, Bayesian Multivariate Logistic Regression

Presenter: Lihan He, Presentation

23 May 2008

M.Y. Park and T. Hastie, Penalized Logistic Regression for Detecting Gene Interactions

Presenter: Minhua Chen, Presentation

30 May 2008

J. Amores, N. Sebe and P. Radeva, Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms

Presenter: Qi An, Presentation

6 June 2008

D.M Blei and J.D. McAuliffe, Supervised Topic Models

Presenter: Iulian Pruteanu, Presentation

13 June 2008

S. Gould, J. Rodgers, D. Cohen, G. Elidan, D. Koller, Multi-Class Segmentation with Relative Location Prior

Presenter: Lan Du, Presentation

20 June 2008

C. Wang, D. Blei and D. Heckerman, Continuous Time Dynamic Topic Models

Presenter: Ivo Shterev, Presentation

27 June 2008

P. Liang and M.I. Jordan, An Asymptotic Analysis of Generative, Discriminative and Pseudolikelihood Estimators

Presenter: Lihan He, Presentation

3 July 2008

G. Chechik, G. Heitz, G. Elidan, P. Abbeel, D. Koller, Max-margin Classification of Data with Absent Features

Presenter: Chunping Wang, Presentation

11 July 2008

E.B. Fox, E.B. Sudderth, M.I. Jordan and A.S. Willsky, An HDP-HMM for Systems with State Persistence

Presenter: Lu Ren, Presentation

18 July 2008

M.B. Wakin and R.G. Baraniuk, Random projections of signal manifolds

C. Hegde, M.B. Wakin and R.G. Baraniuk, Random projections for manifold learning

R.G. Baraniuk and M.B. Wakin, Random projections of smooth manifolds

Presenter: John Paisley, Presentation

25 July 2008

S.J.D. Prince and J.H. Elder, Tied factor analysis for face recognition across large pose changes

Presenter: Lan Du, Presentation

1 August 2008

G. Elidan, B. Packer, G. Heitz and D. Koller, Convex Point Estimation using Undirected Bayesian Transfer Hierarchies

Presenter: Haojun Chen, Presentation

8 August 2008

P. Liang, D. Klein and M.I. Jordan, Agreement-Based Learning

Presenter: Xuejun Liao, Presentation

22 August 2008

M. Girolami and S. Rogers, Variational Bayesian multinomial probit regression with Gaussian priors

Presenter: Minhua Chen, Presentation

29 August 2008

X.Z. Fern and C.E. Brodley, Random Projection for High Dimensional Data Clustering: A Cluster Ensemble Approach

Presenter: Dehong Liu, Presentation

5 September 2008

K.T. Miller, T.L. Griffiths and M.I. Jordan, The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features

Presenter: John Paisley, Presentation

12 September 2008

T.L. Griffiths, M. Steyvers, D.M. Blei and J.B. Tenenbaum, Integrating Topics and Syntax

Preseneter: Eric Wang, Presentation

19 September 2008

L. Meier, S. van de Geer and P. Buhlmann, The Group Lasso for Logistic Regression

Presenter: Lu Ren, Presentation

3 October 2008

P. Poupart and N. Vlassis, Model-based Bayesian Reinforcement Learning in Partially Observable Domains

Presenter: Lihan He, Presentation

17 October 2008

P. Indyk and R. Motwani, Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality

Presenter: Dehong Liu, Presentation

24 October 2008

J.A. Duan, M. Guindani and A.E. Gelfand, Generalized Spatial Dirichlet Process Models

Presenter: Lu Ren, Presentation

31 October 2008

R. Tibshirani, Regression Shrinkage and Selection via the Lasso

A.E. Hoerl and R.W. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems

Presenter: John Paisley, Presentation

7 November 2008

H. Zou and T. Hastie, Regularization and Variable Selection via the Elastic Net

Presenter: Minhua Chen, Presentation

14 November 2008

J. van Gael, Y. Saatci, Y.W. Teh and Z. Ghahramani, Beam Sampling for the Infinite HMM

Presenter: Lihan He, Presentation

28 November 2009

Y. Gal and A. Pfeffer, Networks of Influence Diagrams: A Formalism for Representing Agents’ Beliefs and Decision Making

Presenter: Chenghui Cai, Presentation

17 December 2008

S. Shringarpure and E.P. Xing, mStruct: A New Admixture Model for Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations

Presenter: Haojun Chen, Presentation

5 January 2009

R. Gomes, M. Welling and P. Perona, Memory Bounded Inference in Topic Models

Presenter: Eric Wang, Presentation

14 January 2009

P. Orbanz and J.M. Buhmann, Smooth Image Segmentation by Nonparametric Bayesian Inference

Presenter: Lan Du, Presentation

30 January 2008

D. Achlioptas, Database Friendly Random Projections

Presenter: Xuejun Liao, Presentation

6 February 2009

M.A.T. Figueiredo, D.S. Cheng and V. Murino, Clustering Under Prior Knowledge with Application to Image Segmentation

Presenter: Lu Ren, Presentation

23 February 2009

G. Sfikas, C. Nikou and N. Galatsanos, Edge Preserving Spatially Varying Mixtures for Image Segmentation

Presenter: Lihan He, Presentation

2 March 2009

A. Gruber, M. Rosen-Zvi and Y. Weiss, Hidden Topic Markov Models

Presenter: Chunping Wang, Presentation

13 March 2009

Y. Qi and T.S. Jaakkola, Parameter Expanded Variational Bayesian Methods

Presenter: John Paisley, Presentation

20 March 2009

H.D. Bondell and B.J. Reich, Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR

Presenter: Minhua Chen, Presentation

27 March 2009

P. Rai and H. Daume III, The Infinite Hierarchical Factor Regression Model

Presenter: Bo Chen, Presentation

3 April 2009

J.B. Tenenbaum, V. de Silva and J.C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction

Presenter: Mingyuan Zhou, Presentation

10 April 2009

A. Krause and C. Guestrin, Near-Optimal Observation Selection Using Submodular Functions

Presenter: Haojun Chen, Presentation

17 April 2009

J. Haupt, R. Castro and R. Nowak, Distilled Sensing: Selective Sampling for Sparse Signal Recovery

Presenter: Lihan He, Presentation

24 April 2009

X. Wang, X. Ma and E. Grimson, Unsupervised Activity Perception by Hierarchical Bayesian Models

Presenter: Xuejun Liao, Presentation

8 May 2009

L.-J. Li, R. Socher and L. Fei-Fei, Towards Total Scene Understanding: Automatic Classification, Annotation and Segmentation

Presenter: Eric Wang, Presentation

22 May 2009

X. Nguyen and A.E. Gelfand, The Dirichlet Labeling Process for Functional Data Analysis

Presenter: Lu Ren, Presentation

1 June 2009

T. Shi, M. Belkin, B. Yu, Data Spectroscopy: Learning Mixture Models using Eigenspaces of Convolution Operators

Presenter: Jorge Silva, Presentation

12 June 2009

A.M. Bruckstein, D.L. Donoho and M. Elad, From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals & Images

Presenter: Mingyuan Zhou , Presentation

19 June 2009

J.M. Duarte-Carvajalino and G. Sapiro, Learning to Sense Sparse Signals

Presenter: Haojun Chen , Presentation

26 June 2009

J. Sivic and A. Zisserman, Efficient Visual Search of Videos Case as Text Retrieval

Presenter: John Paisley, Presentation

3 July 2009

C. Wang, D. Blei and L. Fei-Fei, Simultaneous Image Classification and Annotation

Presenter: Eric Wang, Presentation

10 July 2009

P. Hoff, Simulation of the matrix Bingham-von Mises-Fisher distribution, with applications to multivariate and relational data

Presenter: Chunping Wang, Presentation

17 July 2009

D.B. Dunson, Multivariate Kernel Partition Processes

Presenter: Lan Du, Presentation

24 July 2009

M. Elad and I. Yavneh, A Weighted Average of Sparse Representations is Better than the Sparsest One Alone

Presenter: Dehong Liu, Presentation

31 July 2009

R.P. Adams, I. Murray and D.J.C. MacKay, Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities

Presenter: Lihan He, Presentation

14 August 2009

T. Tieleman and G. Hinton, Using Fast Weights to Improve Persistent Contrastive Divergence

Presenter: Jorge Silva, Presentation

21 August 2009

R.P. Adams and Z. Ghahramani, Archipelago: Nonparametric Bayesian Semi-Supervised Learning

Presenter: Lu Ren, Presentation

4 September 2009

F. Doshi-Velez, K.T. Miller, J. Van Gael and Y.W. Teh, Variational Inference for the Indian Buffet Process

Presenter: John Paisley, Presentation

11 September 2009

N.D. Lawrence and R. Urtasun, Non-linear Matrix Factorization with Gaussian Processes

Presenter: Eric Wang, Presentation

18 September 2009

H. Lee, R. Grosse, R. Ranganath, A.Y. Ng, Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations

Presenter: Mingyuan Zhou, Presentation

25 September 2009

A. Beygelzimer, S. Dasgupta and John Langford, Importance Weighted Active Learning

Presenter: Lingbo Li, Presentation

2 October 2009

F. Doshi-Velez and Z. Ghahramani, Accelerated Sampling for the Indian Buffet Process

Presenter: John Paisley, Presentation

16 October 2009

P. Liang, M.I. Jordan and D. Klein, Learning From Measurements in Exponential Families

Presenter: Haojun Chen, Presentation

23 October 2009

L. Xu, M. White and D. Schuurmans, Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning

Presenter: Chunping Wang, Presentation

30 October 2009

M.J. Choi, V. Chandrasekaran and A.S. Willsky, Exploiting Sparse Markov and Covariance Structure in Multiresolution Models

Presenter: Minhua Chen, Presentation

13 November 2009

K. Yu, J. Lafferty, S. Zhu, Y. Gong, Large-Scale Collaborative Prediction Using a Nonparametric Random Effects Model

Presenter: Xuejun Liao, Presentation

20 November 2009

K.A. Heller and Y.W. Teh and D. Gurur, Infinite Hierarchical Hidden Markov Models

Presenter: Lu Ren, Presentation

18 December 2009

F. Wood and Y.W. Teh, A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation

Presenter: Mingyuan Zhou, Presentation

5 January 2010

Y.W. Teh, A Bayesian Interpretation of Interpolated Kneser-Ney

R. Thibaux and M.I. Jordan, Hierarchical Beta Processes and the Indian Buffet Process

Y.W. Teh and D. Gurur, Indian Buffet Processes with Power-Law Behavior

Presenter: L. Carin, Presentation

15 January 2010

J. Ghosh and D.B. Dunson, Default Priors and Efficient Posterior Computation in Bayesian Factor Analysis

Presenter: Eric Wang, Presentation

22 January 2010

D. Hsu, S.M. Kakade, J. Langford and T. Zhang, Multi-Label Prediction via Compressed Sensing

Presenter: Lingbo Li, Presentation

29 January 2010

H.F. Lopes, E. Salazar and D. Gamerman, Spatial Dynamic Factor Analysis

Presenter: Zhengming.Xing, Presentation

12 February 2010

P.J. Green and D.I. Hastie, Reversible Jump MCMC

Presenter: Miao Liu, Presentation

19 February 2010

K. Bush and J. Pineau, Manifold Embeddings for Model-Based Reinforcement Learning Under Partial Observability

Presenter: Chenghui Cai, Presentation

26 February 2010

J. Luttinen and A. Ilin, Variational Gaussian-Process Factor Analysis for Modeling Spatio-Temporal Data

Presenter: Bo Chen, Presentation

5 March 2010

H.M. Wallach, D. Minno and A. McCullum, Rethinking LDA: Why Priors Matter

Presenter: Eric Wang, Presentation

12 March 2010

E.B. Fox, E.B. Sudderth, M.I. Jordan and A.S. Willsky, Sharing Features Among Dynamical Systems With Beta Processes

Presenter: Haojun Chen, Presentation

19 March 2010

C. Wang and D.M. Blei, Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process

Presenter: Chunping Wang, Presentation

2 April 2010

T. Iwata, T. Yamada and N. Ueda, Modeling Social Annotation Data With Content Relevance Using a Topic Model

Presenter: Jorge Silva, Presentation

9 April 2010

J. Mairal, F. Bach, J. Ponce, G. Sapiro and A. Zisserman, Non-Local Sparse Models for Image Restoration

Presenter: Mingyuan Zhou, Presentation

16 April 2010

O-A. Maillard and R. Munos, Compressed Least-Squares Regression

Presenter: Minhua Chen, Presentation

23 April 2010

S. Gould, T. Gao and D. Koller, Region-Based Segmentation and Object Detection

Presenter: Eric Wang, Presentation

30 April 2010

F. Doshi-Velez, The Infinite Partially Observable Markov Decision Process

Presenter: Xuejun Liao, Presentation

7 May 2010

H. Lee, Y. Largman, P. Pham and A.Y. Ng, Unsupervised Feature Learning for Audio Classification Using Convolutional Deep Belief Networks

Presenter: Bo Chen, Presentation

14 May 2010

D. Krishnan and R. Fergus, Fast Image Deconvolution Using Hyper-Laplacian Priors

Presenter: Zhengming.Xing, Presentation

21 May 2010

A.C. Courville, D. Eck and Y. Bengio, An Infinite Factor Modeling Hierarchy via a Noisy-Or Mechanism

Presenter: Lingbo Li, Presentation

28 May 2010

Y. Chen, M. Kapralpw, D. Pavlov and J.E. Canny, Factor Modeling for Advertisement Targeting

Presenter: Miao Liu, Presentation

4 June 2010

K.T. Miller, T.L. Griffiths and M.I. Jordan, Nonparametric Latent Feature Models for Link Prediction

Presenter: Minhua Chen, Presentation

11 June 2010

R. Jenatton, J. Mairal, G. Obozinski and F. Bach, Proximal Methods for Sparse Hierarchical Dictionary Learning

Presenter: Bo Chen, Presentation

18 June 2010

P. Smaragdis, M. Shashanka and B. Raj, A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds

Presenter: Priyadip Ray, Presentation

25 June 2010

V. Rao and Y.W. Teh, Spatial Normalized Gamma Processes

Presenter: Eric Wang, Presentation

2 July 2010

M.N. Schmidt, Linearly Constrained Bayesian Matrix Factorization for Blind Source Separation

Presenter: Jorge Silva, Presentation

9 July 2010

R.P. Adams, H.M. Wallach and Z. Ghahramani, Learning the Structure of Deep Sparse Graphical Models

Presenter: Zhengming Xing, Presentation

16 July 2010

P. Rai and H. Daume III, Model-Label Prediction via Sparse Infinite CCA

Presenter: Lingbo Li, Presentation

23 July 2010

S. Bengio, F. Pereira, Y. Singer and D. Strelow, Group Sparse Coding

Presenter: Miao Liu, Presentation

30 July 2010

J. Vanhatalo, P. Jylanki and A. Vehtari, Gaussian Process Regression With Student-t Likelihood

Presenter: Minhua Chen, Presentation

6 August 2010

S.-H. Yang, H. Zha and B.-G. Hu, Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora

Presenter: Haojun Chen, Presentation

13 August 2010

L. Zhu, Y. Chen, W. Freeman and A. Torralba, Nonparametric Bayesian Texture Learning and Synthesis

Presenter: Eric Wang, Presentation

20 August 2010

Y.L. Boureau, F. Bach, Y. LeCun and J. Ponce, Learning Mid-Level Features for Recognition

Presenter: Bo Chen, Presentation

3 September 2010

J. Yang, K. Yu and T. Huang, Supervised Translation-Invariant Sparse Coding

Presenter: Jorge Silva, Presentation

10 September 2010

R. Jenatton, G. Obozinski and F. Bach, Structured Sparse Principal Component Analysis

Presenter: Xuejun Liao, Presentation

17 September 2010

K. Yu, T. Zhang and Y. Gong, Nonlinear Learning Using Local Coordinate Coding

K. Yu and T. Zhang, Improved Local Coordinate Coding Using Local Tangents

J. Wang, J. Yang, K. Yu, F. Lv, T. Huang and Y. Gong, Locality-Constrained Linear Coding for Image Classification

Presenter: Mingyuan Zhou, Presentation

24 September 2010

M.D. Hoffman, D.M. Blei and P.R. Cook, Bayesian Nonparametric Matrix Factorization for Recorded Music

Presenter: Lu Ren, Presentation

1 October 2010

A. Rodriguez, D.B. Dunson and A.E. Gelfand, Latent Stick-Breaking Processes

Presenter: Esther Salazar, Presentation

8 October 2010

R. Yoshida and M.West, Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing

Presenter: Miao Liu, Presentation

15 October 2010

C.M. Carvalho, N.G. Polson and J.G. James, The horseshoe estimator for sparse signals

Presenter: Eric Wang, Presentation

22 October 2010

J. Chang and D.M. Blei, Hierarchical Relational Models for Document Networks

Presenter: Haojun Chen, Presentation

5 November 2010

J. Friedman, T. Hastie and R. Tibshirani, Sparse Inverse Covariance Estimation with the Graphical Lasso

N. Stadler and P. Buhlmann, Missing Values: Sparse Inverse Covariance Estimation and an Extension to Sparse Regression

O. Banerjee, L. El Ghaoui and A. d’Aspremont, Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data

N. Meinshausen and P. Buhlmann, High-Dimensional Graphs and Variable Selection with the Lasso

Presenter: Minhua Chen, Presentation

17 November 2010

N. Bartlett, D. Pfau, F. Wood, Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process

Presenter: Yingjian Wang, Presentation

24 November 2010

R.P. Adams, Z. Ghahramani and M.I. Jordan, Tree-Structured Stick Breaking Processes for Hierarchical Data

Presenter: XianXing Zhang, Presentation

3 December 2010

Y.L. Boureau, J. Ponce and Y. LeCun, A Theoretical Analysis of Feature Pooling in Visual Recognition

Presenter: Bo Chen, Presentation

13 December 2010

K. Jarrett, K. Kavukcuoglu, M.A. Ranzato and Y. LeCun, What is the Best Multi-Stage Architecture for Object Recognition?

Presenter: Lingbo Li, Presentation

20 December 2010

N. Joshi and M. Brady, Non-Parametric Mixture Modeling Based Evolution of Level Sets and Application to Medical Images

Presenter: Lu Ren, Presentation

7 January 2011

J. Zhu, A. Ahmed and E.P. Xing, MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification

Presenter: Haojun Chen, Presentation

14 January 2011

J. Zhu and E.P. Xing, Conditional Topic Random Fields

Presenter: Eric Wang, Presentation

21 January 2011

J. Gasthaus, F. Wood, Yee Whye Teh, Lossless Compression Based on the Sequence Memoizer

Presenter: Yingjian Wang, Presentation

18 February 2011

N. Srebro and T. Jaakkola, Weighted Low-Rank Approximations

Presenter: Mingyuan Zhou , Presentation

25 February 2011

A. Torralba, K.P. Murphy and W.T. Freeman, Sharing Visual Features for Multiclass and Multiview Object Detection

Presenter: Jorge Silva, Presentation

4 March 2011

A. McCallum, X. Wang and A. Corrada-Emmanuel, Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email

Presenter: Miao Liu, Presentation

11 March 2011

F. Lin and W.W. Cohen, Power Iteration Clustering

Presenter: Minhua Chen, Presentation

25 March 2011

Y. Zhang and J. Schneider, Learning Multiple Tasks with a Sparse Matrix-Normal Prior

Presenter: Esther Salazar, Presentation

1 April 2011

K. Kavukcuoglu, P. Sermanet, Y.L. Boureau, K. Gregor, M. Mathieu, Y. LeCun, Learming Convolutional Feature Hierarchies for Visual Recognition

Presenter: Bo Chen, Presentation

8 April 2011

J. Mairal, F. Bach, J. Ponce, G. Sapiro, Online Learning for Matrix Factorization and Sparse Coding

Presenter: Haojun Chen, Presentation

15 April 2011

M.D. Hoffman, D.B. Blei and F. Bach, Online Learning for Latent Dirichlet Allocation

Presenter: Lingbo Li, Presentation

22 April 2011

J. Leskovec, D. Chakrabarti, J. Kleinberg, C. Faloutsos, Z. Ghahramani, Kronecker Graphs: An Approach to Modeling Networks

Presenter: Eric Wang, Presentation

29 April 2011

A. Canale and D.B. Dunson, Bayesian Kernel Mixtures for Counts

Presenter: Yingjian Wang, Presentation

6 May 2011

H. Ishwaaran and J.S. Rao, Spike and Slab Variable Selection: Frequentist and Bayesian Strategies

Presenter: Minhua Chen, Presentation

13 May 2011

K. Weinberger and O. Chapelle, Large Margin Taxonomy Embedding with an Application to Document Categorization

Presenter: Jorge Silva, Presentation

20 May 2011

S. Bengio, J. Weston and D. Grangier, Label Embedding Trees for Large Multi-Class Tasks

Presenter: Zhengming Xing, Presentation

3 June 2011

D. Lin, E. Grimson and J. Fisher, Construction of Dependent Dirichlet Processes Based on Poisson Processes

Presenter: Yingjian Wang, Presentation

10 June 2011

R. Salakhutdinov, J. Tenenbaum and A. Torralba, One-Shot Learning with a Hierarchical Nonparametric Bayesian Model

Presenter: Esther Salazar, Presentation

17 June 2011

A. Coates, H. Lee and A.Y. Ng, An Analysis of Single-Layer Networks in Unsupervised Feature Learning

A. Coates and A.Y. Ng, The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization

Presenter: Mingyuan Zhou, Presentation

24 June 2011

J. Kallsen and P. Tankovy, Characterization of Dependence of Multidimensional Lévy Processes Using Lévy Copulas

Presenter: Yingjian Wang, Presentation

8 July 2011

A.L. Chambers, P. Smyth and M. Steyvers, Learning Concept Graphs from Text with Stick-Breaking Priors

Presenter: Lingbo Li, Presentation

15 July 2011

J. Paisley, C. Wang and D. Blei, The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling

Presenter: Minhua Chen, Presentation

25 July 2011

B.P. Carlin and A. E. Gelfand, An Iterative Monte Carlo Method for Nonconjugate Bayesian Analysis

P. Muller, A Generic Approach to Posterior Integration and Gibbs Sampling

J.S. Liu, Metropolized Independent Sampling with Comparisons to Rejection Sampling and Importance Sampling

Presenter: Mingyuan Zhou, Presentation

5 August 2011

A. Ahmed and E.P. Xing, Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream

Presenter: Bo Chen, Presentation

12 August 2011

R. M. Neal, Slice Sampling

Presenter: Priyadip Ray, Presentation

19 August 2011

C.M. Carvalho, H.F. Lopes, N.G. Polson and M.A. Taddy, Particle Learning for General Mixtures

N. Chopin, A. Iacobucci, J.-M. Marin, K. L. Mengersen, C. P. Robert, R. Ryder, and C. Schafer, On Particle Learning

Presenter: Miao Liu, Presentation

26 August 2011

I. Sutskever, R. Salakhutdinov, J.B. Tenenbaum, Modeling Relational Data Using Bayesian Clustered Tensor Factorization

Presenter: Esther Salazar, Presentation

2 September 2011

A.P. Singh and G.J. Gordon, A Bayesian Matrix Factorization Model for Relational Data

A.P. Singh and G.J. Gordan, Relational Learning via Collective Matrix Factorization

Presenter: XianXing Zhang, Presentation

16 September 2011

S. Williamson, C. Wang, K.A. Heller and D.M. Blei, The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling

Presenter: Eric Wang, Presentation

23 September 2011

L.-J. Li, C. Wang, Y. Lim, D.M. Blei, L. Fei-Fei, Building and Using a Semantivisual Image Hierarchy

Presenter: Lingbo Li, Presentation

3 October 2011

A. Geramifard, F. Doshi, J. Redding, N. Roy, and J.P. How, Online Discovery of Feature Dependencies

Presenter: Xuejun Liao, Presentation

10 October 2011

M. Dud´ık, J. Langford and L. Li, Doubly Robust Policy Evaluation and Learning

Presenter: Miao Liu, Presentation

17 October 2011

M. Welling and Y.W. Teh, Bayesian Learning via Stochastic Gradient Langevin Dynamics

Presenter: David Carlson, Presentation

26 October 2011

F. Doshi-Velez, D. Wingate, J. Tenenbaum and N. Roy, Infinite Dynamic Bayesian Networks

Presenter: Mingyuan Zhou, Presentation

4 November 2011

D.L. Donoho, A. Maleki and A. Montanari, Message Passing Algorithms for Compressed Sensing: I. Motivation and Construction

D.L. Donoho, A. Maleki and A. Montanari, Message Passing Algorithms for Compressed Sensing: II. Analysis and Validation

Presenter: Nate Strawn, Presentation

11 November 2011

A. Banerjee, D. Dunson and S. Tokdar, Efficient Gaussian Process Regression for Large Data Sets

Presenter: Priyadip Ray, Presentation

18 November 2011

L. Wang and D.B. Dunson, Fast Bayesian Inference in Dirichlet Process Mixture Models

Presenter: Esther Salazar, Presentation

2 December 2011

A. Agovic, A. Banarjee and S. Chatterjee, Probabilistic Matrix Addition

Presenter: Lingbo Li, Presentation

9 December 2011

J. Zhu and T. Hastie, Kernel Logistic Regression and the Import Vector Machine

Presenter: Ding Mingtao, Presentation

16 December 2011

F. Liang, K. Miao, M. Liao, S. Mukherjee and M. West, Nonparametric Bayesian Kernel Models

Presenter: Yingjian Wang, Presentation

13 January 2012

Z. Zhang, G. Dai and M.I. Jordan, Bayesian Generalized Kernel Mixed Models

Presenter: Priyadip Ray, Presentation

20 January 2012

N.S. Pillai, Q. Wu, F. Liang, S. Mukherjee andR.L. Wolpert,Characterizing the Function Space for Bayesian Kernel Models

Presenter: Mingyuan Zhou, Presentation

27 January 2012

L. Zhang, C. Chen, J. Bu, D. Cai, X. He, T.S. Huang, Active Learning Based on Locally Linear Reconstruction

Presenter: Minhua Chen, Presentation

3 February 2012

N. Friedman and D. Koller, Being Bayesian About Network Structure: A Bayesian Approach to Structure Discovery in Bayesian Networks

Presenter: XianXing Zhang, Presentation

10 February 2012

N.G. Polson and J.G. Scott, Local Shrinkage Rules, Levy Processes, and Regularized Regression

Presenter: David Carlson, Presentation

17 February 2012

M. Kolar, J. Lafferty and L. Wasserman, Union Support Recovery in Multi-task Learning

Presenter: Shaobo Han, Presentation

2 March 2012

Y. Hitomi, J. Gu, M. Gupta, T. Mitsunaga and S. K. Nayar, Video from a Single Coded Exposure Photograph using a Learned Over-Complete Dictionary

Presenter: Ajit Rajwade, Presentation

9 March 2012

M. Harel and S. Mannor, Learning from Multiple Outlooks

B. Kulis, K. Saenko and T. Darrel, What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms

Presenter: Minhua Chen, Presentation

16 March 2012

A. Armagan, D.B. Dunson and J. Lee, Generalized double Pareto shrinkage

Presenter: Esther Salazar, Presentation

30 March 2012

A. Bhattacharya and D.B. Dunson, Sparse Bayesian infinite factor models

Presenter: XianXing Zhang, Presentation

6 April 2012

E. Grave, G. Obozinski and F. Bach, Trace Lasso: a trace norm regularization for correlated designs

Presenter: Zhengming Xing, Presentation

13 April 2012

H. Rue and S. Martino, Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

Presenter: Esther Salazar, Presentation

20 April 2012

O. Dikmen and C. Fevotte, Nonnegative Dictionary Learning in the Exponential Noise Model for Adaptive Music Signal Representation

Presenter: Ding Mingtao, Presentation

7 May 2012

F. Niu, B. Recht, C. Re and S.J. Wright, A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Presenter: David Carlson, Presentation

14 May 2012

Z. James, X. Hao Xu and P.J. Ramadge, Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries

Presenter: David Lue, Presentation

21 May 2012

A.C. Sankaranarayanan, P.K. Turaga, R. Chellappa, and R.G. Baraniuk, Compressive Acquisition of Dynamical Scenes

Presenter: Ajit Rajwade, Presentation

4 June 2012

T. Zhou, H. Shan, A. Banerjee, G. Sapiro, Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information

Presenter: Jorge Silva, Presentation

11 June 2012

A. Rodriguez and K. Ghosh, Nested Partition Models

Presenter: Esther Salazar, Presentation

18 June 2012

D. Zoran and Y, Weiss, From Learning Models of Natural Image Patches to Whole Image Restoration

Presenter: Eric Wang, Presentation

6 July 2012

Z. Xu, F. Yan and Y. Qi, Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis

Presenter: Joe Ryu, Presentation

13 July 2012

Z. Yang, C. Zhang and L. Xie, Robustly Stable Signal Recovery in Compressed Sensing with Structured Matrix Perturbation

Presenter: Minhua Chen, Presentation

20 July 2012

P. Bachman and D. Precup, Improved Estimation in Time Varying Models

Presenter: Zhengming Xing, Presentation

27 July 2012

G. Brown, A. Pocock, M.-J. Zhao and M. Lujan, Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection

Presenter: Wenzhao Lian, Presentation

3 August 2012

J. Bruna and S. Mallat, Invariant Scattering Convolution Networks

Presenter: Bo Chen, Presentation

15 August 2012

Y. Bachrach, T. Minka, J. Guiver and T. Graepel, How To Grade a Test Without Knowing the Answers: A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing

Presenter: David Carlson, Presentation

24 August 2012

J. Zhu, A. Ahmed, E.P. Xing, MedLDA: Maximum Margin Supervised Topic Models

Presenter: Zhengming Xing, Presentation

31 August 2012

A. Jalali and Sujay Sanghavi, Learning the Dependence Graph of Time Series with Latent Factors

Presenter: Xin Yuan, Presentation

7 September 2012

Y. Tang, R. Salakhutdinov and G. Hinton, Deep Mixtures of Factor Analysers

Presenter: Jianbo Yang, Presentation

14 September 2012

B. Cseke and T. Heskes, Improving Posterior Marginal Approximations in Latent Gaussian Models

B. Cseke and T. Heskes, Approximate Marginals in Latent Gaussian Models

Presenter: Shaobo Han, Presentation

21 September 2012

P. Sprechmann, A. Bronstein and G. Sapiro, Learning Efficient Structured Sparse Models

Presenter: Yingjian Wang, Presentation

28 September 2012

J. Zhu, Max-Margin Nonparametric Latent Feature Models for Link Prediction

Presenter: XianXing Zhang, Presentation

5 October 2012

C. Farabet, C. Couprie, L. Najman and Y. LeCun, Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers

Presenter: Bo Chen, Presentation

15 October 2012

T.P. Minka, R. Xiang and Y. Qi, Virtual Vector Machine for Bayesian Online Classification

Presenter: Lingbo Li, Presentation

24 October 2012

C. Chen, N. Ding and W. Buntine, Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling

Presenter: Mingyuan Zhou, Presentation

6 November 2012

R. Peharz and F. Pernkopf, Exact Maximum Margin Structure Learning of Bayesian Networks

Presenter: Miao Liu, Presentation

16 November 2012

Y. Shi and Fei Sha, Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation

Presenter: Liming Wang, Presentation

26 November 2012

N. Le Roux, M. Schmidt and F. Bach, A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets

Presenter: Miao Liu, Presentation

30 November 2012

C. Bracegirdle and D. Barber, Bayesian Conditional Cointegration

Presenter: Jianbo Yang

7 December 2012

J. Paisley, C. Wang, D.M. Blei and M.I. Jordan, Nested Hierarchical Dirichlet Processes

Presenter: David Carlson

14 December 2012

A. Joulin and F. Bach, A convex relaxation for weakly supervised classifiers

Presenter: Joe Ryu

21 December 2012

J. Paisley, D.M. Blei, M.I. Jordan, Variational Bayesian Inference with Stochastic Search

Presenter: Mingyuan Zhou

28 December 2012

M.J. Paul and M. Dredze, Factorial LDA: Sparse Multi-Dimensional Text Models

Presenter: Lingbo Li

4 January 2013

C. Wang and D. Blei, Truncation-free Stochastic Variational Inference for Bayesian Nonparametric Models

Presenter: XianXing Zhang

11 January 2013

I.J. Goodfellow, A. Courville and Y. Bengio, Large-Scale Feature Learning With Spike-and-Slab Sparse Coding

Presenter: Bo Chen

18 January 2013

A. Ahmed, S. Ravi, S.M. Narayanamurthy, A.J. Smola, FastEx: Hash Clustering with Exponential Families

Presenter: Shaobo Han

25 January 2013

D.I. Kim, M.C. Hughes and E.B. Sudderth, The Nonparametric Metadata Dependent Relational Model

Presenter: Zhengming Xing

1 February 2013

Y.J. Ko and M. Seeger, Large Scale Variational Bayesian Inference for Structured Scale Mixture Models

Presenter: Mingyuan Zhou

8 February 2013

S. Ahn, A. Korattikara and M. Welling, Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring

Presenter: David Carlson

15 February 2013

D. Mimno, M.D. Hoffman and D.M. Blei, Sparse stochastic inference for latent Dirichlet allocation

Presenter: Miao Liu

22 February 2013

K. Palla, D.A. Knowles and Z. Ghahramani, An Infinite Latent Attribute Model for Network Data

Presenter:

1 March 2013

P. Sarkar, D. Chakrabartiy and M.I. Jordan, Nonparametric Link Prediction in Dynamic Networks

Presenter:

8 March 2013

P. Pletscher and S. Wulff, LPQP for MAP: Putting LP Solvers to Better Use

Presenter:

15 March 2013

S. Balakrishnan, K. Puniyani and J. Lafferty, Sparse Additive Functional and Kernel CCA

Presenter:

22 March 2013

A. Spiliopoulou and A. Storkey, A Topic Model for Melodic Sequences

Presenter:

29 March 2013

R. Garnett, Y. Krishnamurthy, X. Xiong, J. Schneider and R. Mann, Bayesian Optimal Active Search and Surveying

Presenter:

5 April 2012

A. Kumar and H. Daume III, Learning Task Grouping and Overlap in Multi-Task Learning

Presenter:

12 April 2012

H. Liu, F. Han, M. Yuan, J. Lafferty and L. Wasserman, The Nonparanormal SKEPTIC

Presenter:

19 April 2012

M. Xu and J. Lafferty, Conditional Sparse Coding and Grouped Multivariate Regression

Presenter: