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会议/期刊	论文
sigmod2020	PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models.
neurips2021	BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain.
neurips2021	Efficient Truncated Linear Regression with Unknown Noise Variance.
neurips2021	Improving Conditional Coverage via Orthogonal Quantile Regression.
neurips2021	UCB-based Algorithms for Multinomial Logistic Regression Bandits.
neurips2021	Statistical Query Lower Bounds for List-Decodable Linear Regression.
neurips2021	Robust Regression Revisited: Acceleration and Improved Estimation Rates.
neurips2021	Support vector machines and linear regression coincide with very high-dimensional features.
neurips2021	Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex.
neurips2021	Ising Model Selection Using ${\ell }_1$-Regularized Linear Regression: A Statistical Mechanics Analysis.
neurips2021	ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions.
neurips2021	Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions.
neurips2021	Distribution-free inference for regression: discrete, continuous, and in between.
neurips2021	How Data Augmentation affects Optimization for Linear Regression.
neurips2021	Parameter-free HE-friendly Logistic Regression.
neurips2021	A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression.
neurips2021	Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics.
neurips2021	Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime.
neurips2021	Non-Gaussian Gaussian Processes for Few-Shot Regression.
neurips2021	Scalable Quasi-Bayesian Inference for Instrumental Variable Regression.
neurips2021	Out-of-Distribution Generalization in Kernel Regression.
neurips2021	Adversarial Regression with Doubly Non-negative Weighting Matrices.
neurips2021	$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression.
neurips2021	Generic Neural Architecture Search via Regression.
neurips2021	Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem.
neurips2021	Unbalanced Optimal Transport through Non-negative Penalized Linear Regression.
neurips2021	Mixability made efficient: Fast online multiclass logistic regression.
neurips2021	Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression.
neurips2021	Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge.
neurips2021	Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging.
neurips2021	Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding.
neurips2021	Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers.
neurips2021	ReLU Regression with Massart Noise.
neurips2021	Stateful Strategic Regression.
neurips2021	On Optimal Interpolation in Linear Regression.
neurips2021	SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.
neurips2021	A Regression Approach to Learning-Augmented Online Algorithms.
neurips2020	Coresets for Regressions with Panel Data.
neurips2020	Detection as Regression: Certified Object Detection with Median Smoothing.
neurips2020	Online Robust Regression via SGD on the l1 loss.
neurips2020	Dual Instrumental Variable Regression.
neurips2020	Adaptive Reduced Rank Regression.
neurips2020	Robust Meta-learning for Mixed Linear Regression with Small Batches.
neurips2020	Randomized tests for high-dimensional regression: A more efficient and powerful solution.
neurips2020	AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity.
neurips2020	RepPoints v2: Verification Meets Regression for Object Detection.
neurips2020	Neuronal Gaussian Process Regression.
neurips2020	Fair regression with Wasserstein barycenters.
neurips2020	Critic Regularized Regression.
neurips2020	Myersonian Regression.
neurips2020	On the Optimal Weighted ${\ell }_2$ Regularization in Overparameterized Linear Regression.
neurips2020	Truncated Linear Regression in High Dimensions.
neurips2020	Smooth And Consistent Probabilistic Regression Trees.
neurips2020	An implicit function learning approach for parametric modal regression.
neurips2020	Sample complexity and effective dimension for regression on manifolds.
neurips2020	Spike and slab variational Bayes for high dimensional logistic regression.
neurips2020	Deep Evidential Regression.
neurips2020	Non-Crossing Quantile Regression for Distributional Reinforcement Learning.
neurips2020	Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms.
neurips2020	Calibrated Reliable Regression using Maximum Mean Discrepancy.
neurips2020	A convex optimization formulation for multivariate regression.
neurips2020	Fair regression via plug-in estimator and recalibration with statistical guarantees.
neurips2020	Regression with reject option and application to kNN.
neurips2020	LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-resolution and Beyond.
kdd2021	Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression.
kdd2021	When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control.
kdd2020	Residual Correlation in Graph Neural Network Regression.
kdd2020	Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications.
ACMMM2021	Multiple Object Tracking by Trajectory Map Regression with Temporal Priors Embedding.
ACMMM2021	Knowing When to Quit: Selective Cascaded Regression with Patch Attention for Real-Time Face Alignment.
ACMMM2021	Decoupled IoU Regression for Object Detection.
ACMMM2020	Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer.
ACMMM2020	Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking.
ACMMM2020	Region of Interest Based Graph Convolution: A Heatmap Regression Approach for Action Unit Detection.
AAAI2021	Adversarial Pose Regression Network for Pose-Invariant Face Recognitions.
AAAI2021	Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression.
AAAI2021	Longitudinal Deep Kernel Gaussian Process Regression.
AAAI2021	A General Class of Transfer Learning Regression without Implementation Cost.
AAAI2020	OF-MSRN: Optical Flow-Auxiliary Multi-Task Regression Network for Direct Quantitative Measurement, Segmentation and Motion Estimation.
AAAI2020	Regression under Human Assistance.
AAAI2020	Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption.
AAAI2020	Projective Quadratic Regression for Online Learning.
AAAI2020	Pairwise Fairness for Ranking and Regression.
AAAI2020	Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces.
AAAI2020	Improved PAC-Bayesian Bounds for Linear Regression.
AAAI2020	Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization.
AAAI2020	Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression.
AAAI2020	Estimating Stochastic Linear Combination of Non-Linear Regressions.
AAAI2020	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems.
AAAI2020	Causally Denoise Word Embeddings Using Half-Sibling Regression.
AAAI2020	AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation.
AAAI2020	Age Progression and Regression with Spatial Attention Modules.
AAAI2020	Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume.
AAAI2020	Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression.
ICML2021	Sparse Bayesian Learning via Stepwise Regression.
ICML2021	Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients.
ICML2021	Neural Symbolic Regression that scales.
ICML2021	Representation Subspace Distance for Domain Adaptation Regression.
ICML2021	Understanding and Mitigating Accuracy Disparity in Regression.
ICML2021	Consistent regression when oblivious outliers overwhelm.
ICML2021	A Wasserstein Minimax Framework for Mixed Linear Regression.
ICML2021	Online A-Optimal Design and Active Linear Regression.
ICML2021	In-Database Regression in Input Sparsity Time.
ICML2021	Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction.
ICML2021	Adapting to misspecification in contextual bandits with offline regression oracles.
ICML2021	Near-Optimal Linear Regression under Distribution Shift.
ICML2021	The Earth Mover’s Pinball Loss: Quantiles for Histogram-Valued Regression.
ICML2021	A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions.
ICML2021	Oblivious Sketching for Logistic Regression.
ICML2021	Inference for Network Regression Models with Community Structure.
ICML2021	Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression.
ICML2021	Training Data Subset Selection for Regression with Controlled Generalization Error.
ICML2021	Asymptotics of Ridge Regression in Convolutional Models.
ICML2021	A Precise Performance Analysis of Support Vector Regression.
ICML2021	Delving into Deep Imbalanced Regression.
ICML2020	Safe screening rules for L0-regression from Perspective Relaxations.
ICML2020	Model-Based Reinforcement Learning with Value-Targeted Regression.
ICML2020	Fast OSCAR and OWL Regression via Safe Screening Rules.
ICML2020	Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks.
ICML2020	Boosted Histogram Transform for Regression.
ICML2020	On Coresets for Regularized Regression.
ICML2020	Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors.
ICML2020	Randomly Projected Additive Gaussian Processes for Regression.
ICML2020	Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles.
ICML2020	Partial Trace Regression and Low-Rank Kraus Decomposition.
ICML2020	Meta-learning for Mixed Linear Regression.
ICML2020	Nearly Linear Row Sampling Algorithm for Quantile Regression.
ICML2020	Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation.
ICML2020	Causal Strategic Linear Regression.
ICML2020	One-shot Distributed Ridge Regression in High Dimensions.
ICML2020	Piecewise Linear Regression via a Difference of Convex Functions.
ICML2020	Logistic Regression for Massive Data with Rare Events.
ICML2020	Optimal Estimator for Unlabeled Linear Regression.
ICML2020	Smaller, more accurate regression forests using tree alternating optimization.
ICML2019	AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs.
ICML2019	Fair Regression: Quantitative Definitions and Reduction-Based Algorithms.
ICML2019	Rates of Convergence for Sparse Variational Gaussian Process Regression.
ICML2019	Dimensionality Reduction for Tukey Regression.
ICML2019	Improved Convergence for ${\ell }_1$ and ${\ell }_{\hat{a}}ˆ\check{z}$ Regression via Iteratively Reweighted Least Squares.
ICML2019	Distribution calibration for regression.
ICML2019	On Sparse Linear Regression in the Local Differential Privacy Model.
ICML2019	Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering.
ICLR2020	Learning Disentangled Representations for CounterFactual Regression.
ICLR2020	Dynamic Time Lag Regression: Predicting What & When.
ICLR2020	Ridge Regression: Structure, Cross-Validation, and Sketching.
ICLR2021	Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients.
ICLR2021	Knowledge distillation via softmax regression representation learning.
ICLR2021	Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors.
ICLR2021	On the Universality of the Double Descent Peak in Ridgeless Regression.
ICLR2021	Using latent space regression to analyze and leverage compositionality in GANs.
ICLR2021	Learning Deep Features in Instrumental Variable Regression.
ICLR2021	A Hypergradient Approach to Robust Regression without Correspondence.
ICLR2021	Dataset Meta-Learning from Kernel Ridge-Regression.
CVPR2021	Progressive Contour Regression for Arbitrary-Shape Scene Text Detection.
CVPR2021	CapsuleRRT: Relationships-Aware Regression Tracking via Capsules.
CVPR2021	Geo-FARM: Geodesic Factor Regression Model for Misaligned Pre-Shape Responses in Statistical Shape Analysis.
CVPR2021	Rethinking the Heatmap Regression for Bottom-Up Human Pose Estimation.
CVPR2021	AGORA: Avatars in Geography Optimized for Regression Analysis.
CVPR2021	Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression.
CVPR2021	Positive-Congruent Training: Towards Regression-Free Model Updates.
CVPR2021	Bottom-Up Human Pose Estimation via Disentangled Keypoint Regression.
CVPR2021	GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation.
CVPR2020	Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution.
CVPR2020	SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking.
CVPR2020	3D Human Mesh Regression With Dense Correspondence.
CVPR2020	Probabilistic Regression for Visual Tracking.
CVPR2020	Dense Regression Network for Video Grounding.
CVPR2020	Hierarchical Scene Coordinate Classification and Regression for Visual Localization.
CVPR2020	Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection.
CVPR2020	Mixture Dense Regression for Object Detection and Human Pose Estimation.
CVPR2020	Regularizing CNN Transfer Learning With Randomised Regression.
CVPRW2021	A Mathematical Analysis of Learning Loss for Active Learning in Regression.
CVPRW2021	3D Fiber Segmentation With Deep Center Regression and Geometric Clustering.
CVPRW2020	Extending Absolute Pose Regression to Multiple Scenes.
CVPRW2020	ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization.
CVPRW2020	Deep Regression for Imaging Solar Magnetograms using Pyramid Generative Adversarial Networks.
CVPRW2020	Hierarchical Regression Network for Spectral Reconstruction from RGB Images.
ICCV2021	Learning Multi-Scene Absolute Pose Regression with Transformers.
ICCV2021	Generalized Shuffled Linear Regression.
ICCV2021	Group-aware Contrastive Regression for Action Quality Assessment.
ICCV2021	Human Pose Regression with Residual Log-likelihood Estimation.
ICCV2021	Removing the Bias of Integral Pose Regression.
ICCV2021	Monocular, One-stage, Regression of Multiple 3D People.
ICCV2021	PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop.
ICCV2021	H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression.
ICCV2021	An investigation of attention mechanisms in histopathology whole-slide-image analysis for regression objectives.
ICCV2021	FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integration.
ICCV2019	DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks.
ICCV2019	Instance-Level Future Motion Estimation in a Single Image Based on Ordinal Regression.
ICCV2019	A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation From a Single Depth Image.
ICCV2019	Image Aesthetic Assessment Based on Pairwise Comparison ­ A Unified Approach to Score Regression, Binary Classification, and Personalization.
ICCV2019	Probabilistic Deep Ordinal Regression Based on Gaussian Processes.
ICCV2019	Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression.
ICCV2019	Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation.
ACL2021	Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates.
ACL2021	Survival text regression for time-to-event prediction in conversations.
IJCAI2021	AgeFlow: Conditional Age Progression and Regression with Normalizing Flows.
IJCAI2021	SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking.
IJCAI2021	Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic.
IJCAI2021	Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning.
IJCAI2021-aisafety	An Adversarial Attacker for Neural Networks in Regression Problems.
IJCAI2020	Online Semi-supervised Multi-label Classification with Label Compression and Local Smooth Regression.
IJCAI2020	Scalable Gaussian Process Regression Networks.
IJCAI2020	Sinkhorn Regression.
IJCAI2020	Deep Hurdle Networks for Zero-Inflated Multi-Target Regression: Application to Multiple Species Abundance Estimation.
IJCAI2020	An Interactive Visualization Platform for Deep Symbolic Regression.
TPAMI2022	Learning Meta-Distance for Sequences by Learning a Ground Metric via Virtual Sequence Regression.
TPAMI2022	Enhanced Group Sparse Regularized Nonconvex Regression for Face Recognition.
TPAMI2021	Nonlinear Regression via Deep Negative Correlation Learning.
TPAMI2021	Correction to “Nonlinear Regression via Deep Negative Correlation Learning”.
TPAMI2021	Acceleration of Non-Rigid Point Set Registration With Downsampling and Gaussian Process Regression.
TPAMI2020	Approximate Sparse Multinomial Logistic Regression for Classification.
TPAMI2020	Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning.
TPAMI2020	Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection.
TPAMI2020	A Comprehensive Analysis of Deep Regression.
TPAMI2020	Confidence Propagation through CNNs for Guided Sparse Depth Regression.
IJCV2022	Robust Geodesic Regression.
IJCV2022	Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks.
IJCV2021	Entrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography.
IJCV2021	Learning Regression and Verification Networks for Robust Long-term Tracking.
IJCV2020	Masked Linear Regression for Learning Local Receptive Fields for Facial Expression Synthesis.
IJCV2020	CR-Net: A Deep Classification-Regression Network for Multimodal Apparent Personality Analysis.
JMLR2022	Interpolating Predictors in High-Dimensional Factor Regression.
JMLR2022	Spatial Multivariate Trees for Big Data Bayesian Regression.
JMLR2022	An improper estimator with optimal excess risk in misspecified density estimation and logistic regression.
JMLR2021	Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression.
JMLR2021	Sparse Tensor Additive Regression.
JMLR2021	Testing Conditional Independence via Quantile Regression Based Partial Copulas.
JMLR2021	Histogram Transform Ensembles for Large-scale Regression.
JMLR2021	Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression.
JMLR2021	Non-parametric Quantile Regression via the K-NN Fused Lasso.
JMLR2021	Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model.
JMLR2021	Optimal Rates of Distributed Regression with Imperfect Kernels.
JMLR2021	Unlinked Monotone Regression.
JMLR2021	Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond.
JMLR2021	Differentially Private Regression and Classification with Sparse Gaussian Processes.
JMLR2021	Soft Tensor Regression.
JMLR2021	Classification vs regression in overparameterized regimes: Does the loss function matter?
JMLR2021	Consistency of Gaussian Process Regression in Metric Spaces.
JMLR2021	Statistically and Computationally Efficient Change Point Localization in Regression Settings.
JMLR2021	Inference for the Case Probability in High-dimensional Logistic Regression.
JMLR2020	A Statistical Learning Approach to Modal Regression.
JMLR2020	Online Sufficient Dimension Reduction Through Sliced Inverse Regression.
JMLR2020	Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables.
JMLR2020	WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions.
JMLR2020	Distributed Kernel Ridge Regression with Communications.
JMLR2020	Prediction regions through Inverse Regression.
JMLR2020	Tensor Regression Networks.
JMLR2020	Convergence of Sparse Variational Inference in Gaussian Processes Regression.
JMLR2020	Empirical Priors for Prediction in Sparse High-dimensional Linear Regression.
JMLR2020	Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information.
JMLR2020	High Dimensional Forecasting via Interpretable Vector Autoregression.
JMLR2020	Distributed High-dimensional Regression Under a Quantile Loss Function.
JMLR2020	Conic Optimization for Quadratic Regression Under Sparse Noise.
JMLR2020	Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models.
JMLR2020	Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data.
JMLR2020	Functional Martingale Residual Process for High-Dimensional Cox Regression with Model Averaging.
TOIS2020	Enhancing Employer Brand Evaluation with Collaborative Topic Regression Models.
TKDE2022	An Online Robust Support Vector Regression for Data Streams.
TKDE2022	Missing Value Imputation via Clusterwise Linear Regression.
TKDE2021	MTBR: Multi-Target Boosting for Regression.
TKDE2021	An Improved Quantum Algorithm for Ridge Regression.
TKDE2021	Nonparametric Regression via Variance-Adjusted Gradient Boosting Gaussian Process Regression.
TKDE2020	Semi-Supervised Feature Selection via Sparse Rescaled Linear Square Regression.
TKDE2020	Anomaly Detection Using Local Kernel Density Estimation and Context-Based Regression.
AI2020	Regression and progression in stochastic domains.