JMLR Volume 23

• Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models

  Subhabrata Majumdar, George Michailidis (1):1−53, 2022 codePDF BibTeX

• Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions

  Shaogao Lv, Heng Lian (2):1−32, 2022 PDF BibTeX

• Recovering shared structure from multiple networks with unknown edge distributions

  Keith Levin, Asad Lodhia, Elizaveta Levina (3):1−48, 2022 PDF BibTeX

• Exploiting locality in high-dimensional Factorial hidden Markov models

  Lorenzo Rimella, Nick Whiteley (4):1−34, 2022 codePDF BibTeX

• Empirical Risk Minimization under Random Censorship

  Guillaume Ausset, Stephan Clémençon, François Portier (5):1−59, 2022 PDF BibTeX

• XAI Beyond Classification: Interpretable Neural Clustering

  Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, Joey Tianyi Zhou (6):1−28, 2022 codePDF BibTeX

• Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes

  Justin D. Silverman, Kimberly Roche, Zachary C. Holmes, Lawrence A. David, Sayan Mukherjee (7):1−42, 2022 codePDF BibTeX

• Deep Learning in Target Space

  Michael Fairbank, Spyridon Samothrakis, Luca Citi (8):1−46, 2022 codePDF BibTeX

• Scaling Laws from the Data Manifold Dimension

  Utkarsh Sharma, Jared Kaplan (9):1−34, 2022 codePDF BibTeX

• Interpolating Predictors in High-Dimensional Factor Regression

  Florentina Bunea, Seth Strimas-Mackey, Marten Wegkamp (10):1−60, 2022 PDF BibTeX

• Near Optimality of Finite Memory Feedback Policies in Partially Observed Markov Decision Processes

  Ali Kara, Serdar Yuksel (11):1−46, 2022 PDF BibTeX

• Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems

  Jayakumar Subramanian, Amit Sinha, Raihan Seraj, Aditya Mahajan (12):1−83, 2022 codePDF BibTeX

• Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality

  Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet (13):1−35, 2022 codePDF BibTeX

• On Generalizations of Some Distance Based Classifiers for HDLSS Data

  Sarbojit Roy, Soham Sarkar, Subhajit Dutta, Anil K. Ghosh (14):1−41, 2022 PDF BibTeX

• A Stochastic Bundle Method for Interpolation

  Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel, M. Pawan Kumar (15):1−57, 2022 codePDF BibTeX

• TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems

  Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Hua Huang, Carola-Bibiane Schönlieb (16):1−48, 2022 codePDF BibTeX

• Spatial Multivariate Trees for Big Data Bayesian Regression

  Michele Peruzzi, David B. Dunson (17):1−40, 2022 codePDF BibTeX

• Decimated Framelet System on Graphs and Fast G-Framelet Transforms

  Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang (18):1−68, 2022 codePDF BibTeX

• Universal Approximation in Dropout Neural Networks

  Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies, Jaron Sanders, Albert Senen-Cerda (19):1−46, 2022 PDF BibTeX

• Supervised Dimensionality Reduction and Visualization using Centroid-Encoder

  Tomojit Ghosh, Michael Kirby (20):1−34, 2022 codePDF BibTeX

• Evolutionary Variational Optimization of Generative Models

  Jakob Drefs, Enrico Guiraud, Jörg Lücke (21):1−51, 2022 codePDF BibTeX

• LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data

  Ali Eshragh, Fred Roosta, Asef Nazari, Michael W. Mahoney (22):1−36, 2022 PDF BibTeX

• Fast and Robust Rank Aggregation against Model Misspecification

  Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama (23):1−35, 2022 PDF BibTeX

• On Biased Stochastic Gradient Estimation

  Derek Driggs, Jingwei Liang, Carola-Bibiane Schönlieb (24):1−43, 2022 PDF BibTeX

• Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting

  Maxime Vono, Daniel Paulin, Arnaud Doucet (25):1−69, 2022 PDF BibTeX

• MurTree: Optimal Decision Trees via Dynamic Programming and Search

  Emir Demirović, Anna Lukina, Emmanuel Hebrard, Jeffrey Chan, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Peter J. Stuckey (26):1−47, 2022 codePDF BibTeX

• Data-Derived Weak Universal Consistency

  Narayana Santhanam, Venkatachalam Anantharam, Wojciech Szpankowski (27):1−55, 2022 PDF BibTeX

• Novel Min-Max Reformulations of Linear Inverse Problems

  Mohammed Rayyan Sheriff, Debasish Chatterjee (28):1−46, 2022 PDF BibTeX

• Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning

  Kaiyi Ji, Junjie Yang, Yingbin Liang (29):1−41, 2022 PDF BibTeX

• A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One

  Augusto Fasano, Daniele Durante (30):1−26, 2022 PDF BibTeX

• An Improper Estimator with Optimal Excess Risk in Misspecified Density Estimation and Logistic Regression

  Jaouad Mourtada, Stéphane Gaïffas (31):1−49, 2022 PDF BibTeX

• Active Learning for Nonlinear System Identification with Guarantees

  Horia Mania, Michael I. Jordan, Benjamin Recht (32):1−30, 2022 PDF BibTeX

• Model Averaging Is Asymptotically Better Than Model Selection For Prediction

  Tri M. Le, Bertrand S. Clarke (33):1−53, 2022 PDF BibTeX

• SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks

  Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu (34):1−29, 2022 codePDF BibTeX

• Optimality and Stability in Non-Convex Smooth Games

  Guojun Zhang, Pascal Poupart, Yaoliang Yu (35):1−71, 2022 PDF BibTeX

• Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization

  Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang (36):1−70, 2022 PDF BibTeX

• Projected Statistical Methods for Distributional Data on the Real Line with the Wasserstein Metric

  Matteo Pegoraro, Mario Beraha (37):1−59, 2022 codePDF BibTeX

• Score Matched Neural Exponential Families for Likelihood-Free Inference

  Lorenzo Pacchiardi, Ritabrata Dutta (38):1−71, 2022 codePDF BibTeX

• (f,Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics

  Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet (39):1−70, 2022 PDF BibTeX

• Structure-adaptive Manifold Estimation

  Nikita Puchkin, Vladimir Spokoiny (40):1−62, 2022 PDF BibTeX

• The Correlation-assisted Missing Data Estimator

  Timothy I. Cannings, Yingying Fan (41):1−49, 2022 PDF BibTeX

• Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks

  Zhong Li, Jiequn Han, Weinan E, Qianxiao Li (42):1−85, 2022 PDF BibTeX

• Sampling Permutations for Shapley Value Estimation

  Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes (43):1−46, 2022 PDF BibTeX

• PAC Guarantees and Effective Algorithms for Detecting Novel Categories

  Si Liu, Risheek Garrepalli, Dan Hendrycks, Alan Fern, Debashis Mondal, Thomas G. Dietterich (44):1−47, 2022 codePDF BibTeX

• Optimal Transport for Stationary Markov Chains via Policy Iteration

  Kevin O'Connor, Kevin McGoff, Andrew B. Nobel (45):1−52, 2022 codePDF BibTeX

• Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent

  Wanrong Zhu, Zhipeng Lou, Wei Biao Wu (46):1−22, 2022 PDF BibTeX

• Cascaded Diffusion Models for High Fidelity Image Generation

  Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans (47):1−33, 2022 codePDF BibTeX

• Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis

  Zhiyan Ding, Shi Chen, Qin Li, Stephen J. Wright (48):1−65, 2022 PDF BibTeX

• Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection

  Xinyi Wang, Lang Tong (49):1−27, 2022 PDF BibTeX

• Analytically Tractable Hidden-States Inference in Bayesian Neural Networks

  Luong-Ha Nguyen, James-A. Goulet (50):1−33, 2022 PDF BibTeX

• Toolbox for Multimodal Learn (scikit-multimodallearn)

  Dominique Benielli, Baptiste Bauvin, Sokol Koço, Riikka Huusari, Cécile Capponi, Hachem Kadri, François Laviolette (51):1−7, 2022 codePDF BibTeX

• LinCDE: Conditional Density Estimation via Lindsey's Method

  Zijun Gao, Trevor Hastie (52):1−55, 2022 PDF BibTeX

• DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python

  Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler (53):1−6, 2022 codePDF BibTeX

• SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

  Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter (54):1−9, 2022 codePDF BibTeX

• Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy

  Terrance D. Savitsky, Matthew R.Williams, Jingchen Hu (55):1−37, 2022 PDF BibTeX

• solo-learn: A Library of Self-supervised Methods for Visual Representation Learning

  Victor Guilherme Turrisi da Costa, Enrico Fini, Moin Nabi, Nicu Sebe, Elisa Ricci (56):1−6, 2022 codePDF BibTeX

• Inherent Tradeoffs in Learning Fair Representations

  Han Zhao, Geoffrey J. Gordon (57):1−26, 2022 PDF BibTeX

• A Statistical Approach for Optimal Topic Model Identification

  Craig M. Lewis, Francesco Grossetti (58):1−20, 2022 PDF BibTeX

• Causal Classification: Treatment Effect Estimation vs. Outcome Prediction

  Carlos Fernández-Loría, Foster Provost (59):1−35, 2022 PDF BibTeX

• A Unifying Framework for Variance-Reduced Algorithms for Findings Zeroes of Monotone operators

  Xun Zhang, William B. Haskell, Zhisheng Ye (60):1−44, 2022 PDF BibTeX

• Sparse Additive Gaussian Process Regression

  Hengrui Luo, Giovanni Nattino, Matthew T. Pratola (61):1−34, 2022 PDF BibTeX

• The AIM and EM Algorithms for Learning from Coarse Data

  Manfred Jaeger (62):1−55, 2022 codePDF BibTeX

• Additive Nonlinear Quantile Regression in Ultra-high Dimension

  Ben Sherwood, Adam Maidman (63):1−47, 2022 PDF BibTeX

• Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity

  Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra (64):1−47, 2022 PDF BibTeX

• On the Complexity of Approximating Multimarginal Optimal Transport

  Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan (65):1−43, 2022 PDF BibTeX

• New Insights for the Multivariate Square-Root Lasso

  Aaron J. Molstad (66):1−52, 2022 codePDF BibTeX

• Are All Layers Created Equal?

  Chiyuan Zhang, Samy Bengio, Yoram Singer (67):1−28, 2022 PDF BibTeX

• Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters

  Wei Zhu, Qiang Qiu, Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng (68):1−45, 2022 PDF BibTeX

• Asymptotic Network Independence and Step-Size for a Distributed Subgradient Method

  Alex Olshevsky (69):1−32, 2022 codePDF BibTeX

• Generalized Sparse Additive Models

  Asad Haris, Noah Simon, Ali Shojaie (70):1−56, 2022 codePDF BibTeX

• Multiple-Splitting Projection Test for High-Dimensional Mean Vectors

  Wanjun Liu, Xiufan Yu, Runze Li (71):1−27, 2022 PDF BibTeX

• Batch Normalization Preconditioning for Neural Network Training

  Susanna Lange, Kyle Helfrich, Qiang Ye (72):1−41, 2022 PDF BibTeX

• A Kernel Two-Sample Test for Functional Data

  George Wynne, Andrew B. Duncan (73):1−51, 2022 PDF BibTeX

• All You Need is a Good Functional Prior for Bayesian Deep Learning

  Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone (74):1−56, 2022 codePDF BibTeX

• Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling

  Gábor Melis, András György, Phil Blunsom (75):1−36, 2022 PDF BibTeX

• Joint Inference of Multiple Graphs from Matrix Polynomials

  Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra (76):1−35, 2022 PDF BibTeX

• Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits

  Lilian Besson, Emilie Kaufmann, Odalric-Ambrym Maillard, Julien Seznec (77):1−40, 2022 codePDF BibTeX

• Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism

  Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos (78):1−49, 2022 PDF BibTeX

• Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors

  Yuling Yao, Aki Vehtari, Andrew Gelman (79):1−45, 2022 PDF BibTeX

• Posterior Asymptotics for Boosted Hierarchical Dirichlet Process Mixtures

  Marta Catalano, Pierpaolo De Blasi, Antonio Lijoi, Igor Pruenster (80):1−23, 2022 PDF BibTeX

• Dependent randomized rounding for clustering and partition systems with knapsack constraints

  David G. Harris, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh (81):1−41, 2022 PDF BibTeX

• FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting

  Boxin Zhao, Y. Samuel Wang, Mladen Kolar (82):1−82, 2022 codePDF BibTeX

• Prior Adaptive Semi-supervised Learning with Application to EHR Phenotyping

  Yichi Zhang, Molei Liu, Matey Neykov, Tianxi Cai (83):1−25, 2022 codePDF BibTeX

• Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior

  Rajarshi Guhaniyogi, Cheng Li, Terrance D. Savitsky, Sanvesh Srivastava (84):1−59, 2022 PDF BibTeX

• A Distribution Free Conditional Independence Test with Applications to Causal Discovery

  Zhanrui Cai, Runze Li, Yaowu Zhang (85):1−41, 2022 PDF BibTeX

• Robust and scalable manifold learning via landmark diffusion for long-term medical signal processing

  Chao Shen, Yu-Ting Lin, Hau-Tieng Wu (86):1−30, 2022 PDF BibTeX

• CD-split and HPD-split: Efficient Conformal Regions in High Dimensions

  Rafael Izbicki, Gilson Shimizu, Rafael B. Stern (87):1−32, 2022 codePDF BibTeX

• Generalized Ambiguity Decomposition for Ranking Ensemble Learning

  Hongzhi Liu, Yingpeng Du, Zhonghai Wu (88):1−36, 2022 PDF BibTeX

• Machine Learning on Graphs: A Model and Comprehensive Taxonomy

  Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy (89):1−64, 2022 PDF BibTeX

• Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling

  Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang (90):1−38, 2022 PDF BibTeX

• When Hardness of Approximation Meets Hardness of Learning

  Eran Malach, Shai Shalev-Shwartz (91):1−24, 2022 PDF BibTeX

• Gauss-Legendre Features for Gaussian Process Regression

  Paz Fink Shustin, Haim Avron (92):1−47, 2022 PDF BibTeX

• Regularized K-means Through Hard-Thresholding

  Jakob Raymaekers, Ruben H. Zamar (93):1−48, 2022 codePDF BibTeX

• Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach

  Kweku Abraham, Ismaël Castillo, Elisabeth Gassiat (94):1−57, 2022 PDF BibTeX

• Attraction-Repulsion Spectrum in Neighbor Embeddings

  Jan Niklas Böhm, Philipp Berens, Dmitry Kobak (95):1−32, 2022 codePDF BibTeX

• Rethinking Nonlinear Instrumental Variable Models through Prediction Validity

  Chunxiao Li, Cynthia Rudin, Tyler H. McCormick (96):1−55, 2022 PDF BibTeX

• Unlabeled Data Help in Graph-Based Semi-Supervised Learning: A Bayesian Nonparametrics Perspective

  Daniel Sanz-Alonso, Ruiyi Yang (97):1−28, 2022 PDF BibTeX

• PECOS: Prediction for Enormous and Correlated Output Spaces

  Hsiang-Fu Yu, Kai Zhong, Jiong Zhang, Wei-Cheng Chang, Inderjit S. Dhillon (98):1−32, 2022 codePDF BibTeX

• Distributed Learning of Finite Gaussian Mixtures

  Qiong Zhang, Jiahua Chen (99):1−40, 2022 codePDF BibTeX

• Total Stability of SVMs and Localized SVMs

  Hannes Köhler, Andreas Christmann (100):1−41, 2022 PDF BibTeX

• Towards An Efficient Approach for the Nonconvex lp Ball Projection: Algorithm and Analysis

  Xiangyu Yang, Jiashan Wang, Hao Wang (101):1−31, 2022 PDF BibTeX

• Sufficient reductions in regression with mixed predictors

  Efstathia Bura, Liliana Forzani, Rodrigo Garcia Arancibia, Pamela Llop, Diego Tomassi (102):1−47, 2022 codePDF BibTeX

• The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures

  Nir Weinberger, Guy Bresler (103):1−79, 2022 PDF BibTeX

• Efficient Least Squares for Estimating Total Effects under Linearity and Causal Sufficiency

  F. Richard Guo, Emilija Perković (104):1−41, 2022 codePDF BibTeX

• Globally Injective ReLU Networks

  Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanić, Maarten de Hoop (105):1−55, 2022 PDF BibTeX

• Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold

  Bokun Wang, Shiqian Ma, Lingzhou Xue (106):1−33, 2022 PDF BibTeX

• IALE: Imitating Active Learner Ensembles

  Christoffer Löffler, Christopher Mutschler (107):1−29, 2022 codePDF BibTeX

• Bayesian subset selection and variable importance for interpretable prediction and classification

  Daniel R. Kowal (108):1−38, 2022 codePDF BibTeX

• Conditions and Assumptions for Constraint-based Causal Structure Learning

  Kayvan Sadeghi, Terry Soo (109):1−34, 2022 PDF BibTeX

• EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation

  Jun Ho Yoon, Seyoung Kim (110):1−39, 2022 codePDF BibTeX

• Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces

  Masaaki Imaizumi, Kenji Fukumizu (111):1−54, 2022 PDF BibTeX

• Sum of Ranked Range Loss for Supervised Learning

  Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu (112):1−44, 2022 codePDF BibTeX

• The Two-Sided Game of Googol

  José Correa, Andrés Cristi, Boris Epstein, José Soto (113):1−37, 2022 PDF BibTeX

• ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction

  Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma (114):1−103, 2022 codePDF BibTeX

• Cauchy–Schwarz Regularized Autoencoder

  Linh Tran, Maja Pantic, Marc Peter Deisenroth (115):1−37, 2022 PDF BibTeX

• An Error Analysis of Generative Adversarial Networks for Learning Distributions

  Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang (116):1−43, 2022 PDF BibTeX

• OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems

  Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer (117):1−45, 2022 codePDF BibTeX

• Under-bagging Nearest Neighbors for Imbalanced Classification

  Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin (118):1−63, 2022 PDF BibTeX

• A spectral-based analysis of the separation between two-layer neural networks and linear methods

  Lei Wu, Jihao Long (119):1−34, 2022 PDF BibTeX

• Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

  William Fedus, Barret Zoph, Noam Shazeer (120):1−39, 2022 codePDF BibTeX

• Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case

  Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander (121):1−38, 2022 PDF BibTeX

• Depth separation beyond radial functions

  Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna (122):1−56, 2022 PDF BibTeX

• Provable Tensor-Train Format Tensor Completion by Riemannian Optimization

  Jian-Feng Cai, Jingyang Li, Dong Xia (123):1−77, 2022 PDF BibTeX

• Darts: User-Friendly Modern Machine Learning for Time Series

  Julien Herzen, Francesco Lässig, Samuele Giuliano Piazzetta, Thomas Neuer, Léo Tafti, Guillaume Raille, Tomas Van Pottelbergh, Marek Pasieka, Andrzej Skrodzki, Nicolas Huguenin, Maxime Dumonal, Jan Kościsz, Dennis Bader, Frédérick Gusset, Mounir Benheddi, Camila Williamson, Michal Kosinski, Matej Petrik, Gaël Grosch (124):1−6, 2022 codePDF BibTeX

• Foolish Crowds Support Benign Overfitting

  Niladri S. Chatterji, Philip M. Long (125):1−12, 2022 PDF BibTeX

• Neural Estimation of Statistical Divergences

  Sreejith Sreekumar, Ziv Goldfeld (126):1−75, 2022 PDF BibTeX

• Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations

  Haoyuan Chen, Liang Ding, Rui Tuo (127):1−32, 2022 PDF BibTeX

• Power Iteration for Tensor PCA

  Jiaoyang Huang, Daniel Z. Huang, Qing Yang, Guang Cheng (128):1−47, 2022 PDF BibTeX

• On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)

  Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, Satish V. Ukkusuri (129):1−46, 2022 PDF BibTeX

• Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks

  Alexander Shevchenko, Vyacheslav Kungurtsev, Marco Mondelli (130):1−55, 2022 PDF BibTeX

• Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence

  Julie Nutini, Issam Laradji, Mark Schmidt (131):1−74, 2022 codePDF BibTeX

• An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference

  Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas (132):1−109, 2022 codePDF BibTeX

• Manifold Coordinates with Physical Meaning

  Samson J. Koelle, Hanyu Zhang, Marina Meila, Yu-Chia Chen (133):1−57, 2022 codePDF BibTeX

• Transfer Learning in Information Criteria-based Feature Selection

  Shaohan Chen, Nikolaos V. Sahinidis, Chuanhou Gao (134):1−105, 2022 codePDF BibTeX

• Recovery and Generalization in Over-Realized Dictionary Learning

  Jeremias Sulam, Chong You, Zhihui Zhu (135):1−23, 2022 PDF BibTeX

• Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization

  Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok (136):1−60, 2022 codePDF BibTeX

• On the Efficiency of Entropic Regularized Algorithms for Optimal Transport

  Tianyi Lin, Nhat Ho, Michael I. Jordan (137):1−42, 2022 PDF BibTeX

• Exact simulation of diffusion first exit times: algorithm acceleration

  Samuel Herrmann, Cristina Zucca (138):1−20, 2022 codePDF BibTeX

• No Weighted-Regret Learning in Adversarial Bandits with Delays

  Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose Blanchet (139):1−43, 2022 PDF BibTeX

• Non-asymptotic and Accurate Learning of Nonlinear Dynamical Systems

  Yahya Sattar, Samet Oymak (140):1−49, 2022 PDF BibTeX

• The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks

  Konstantinos Pantazis, Avanti Athreya, Jesus Arroyo, William N Frost, Evan S Hill, Vince Lyzinski (141):1−77, 2022 PDF BibTeX

• A Perturbation-Based Kernel Approximation Framework

  Roy Mitz, Yoel Shkolnisky (142):1−26, 2022 codePDF BibTeX

• Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning

  Alex A. Gorodetsky, Cosmin Safta, John D. Jakeman (143):1−29, 2022 PDF BibTeX

• A Momentumized, Adaptive, Dual Averaged Gradient Method

  Aaron Defazio, Samy Jelassi (144):1−34, 2022 codePDF BibTeX

• A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning

  Andrew Patterson, Adam White, Martha White (145):1−61, 2022 codePDF BibTeX

• Adversarial Robustness Guarantees for Gaussian Processes

  Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska (146):1−55, 2022 codePDF BibTeX

• On the Robustness to Misspecification of α-posteriors and Their Variational Approximations

  Marco Avella Medina, José Luis Montiel Olea, Cynthia Rush, Amilcar Velez (147):1−51, 2022 PDF BibTeX

• Online Nonnegative CP-dictionary Learning for Markovian Data

  Hanbaek Lyu, Christopher Strohmeier, Deanna Needell (148):1−50, 2022 codePDF BibTeX

• Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning

  Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon (149):1−43, 2022 codePDF BibTeX

• EV-GAN: Simulation of extreme events with ReLU neural networks

  Michaël Allouche, Stéphane Girard, Emmanuel Gobet (150):1−39, 2022 PDF BibTeX

• Universal Approximation of Functions on Sets

  Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner (151):1−56, 2022 PDF BibTeX

• Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning

  Sébastien Forestier, Rémy Portelas, Yoan Mollard, Pierre-Yves Oudeyer (152):1−41, 2022 PDF BibTeX

• Truncated Emphatic Temporal Difference Methods for Prediction and Control

  Shangtong Zhang, Shimon Whiteson (153):1−59, 2022 codePDF BibTeX

• Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach

  Yanwei Jia, Xun Yu Zhou (154):1−55, 2022 codePDF BibTeX

• Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks

  Guy Hacohen, Daphna Weinshall (155):1−46, 2022 PDF BibTeX

• Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification

  Yingying Zhang, Yan-Yong Zhao, Heng Lian (156):1−24, 2022 PDF BibTeX

• A universally consistent learning rule with a universally monotone error

  Vladimir Pestov (157):1−27, 2022 PDF BibTeX

• ktrain: A Low-Code Library for Augmented Machine Learning

  Arun S. Maiya (158):1−6, 2022 codePDF BibTeX

• Structure Learning for Directed Trees

  Martin E. Jakobsen, Rajen D. Shah, Peter Bühlmann, Jonas Peters (159):1−97, 2022 codePDF BibTeX

• Fairness-Aware PAC Learning from Corrupted Data

  Nikola Konstantinov, Christoph H. Lampert (160):1−60, 2022 PDF BibTeX

• Topologically penalized regression on manifolds

  Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Clément Levrard, Wolfgang Polonik (161):1−39, 2022 codePDF BibTeX

• Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods

  Dachao Lin, Haishan Ye, Zhihua Zhang (162):1−40, 2022 PDF BibTeX

• Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements

  Tian Tong, Cong Ma, Ashley Prater-Bennette, Erin Tripp, Yuejie Chi (163):1−77, 2022 codePDF BibTeX

• Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation

  Antoine Dedieu, Rahul Mazumder, Haoyue Wang (164):1−41, 2022 PDF BibTeX

• Improved Classification Rates for Localized SVMs

  Ingrid Blaschzyk, Ingo Steinwart (165):1−59, 2022 PDF BibTeX

• Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

  Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David Sontag (166):1−50, 2022 PDF BibTeX

• Unbiased estimators for random design regression

  Michał Dereziński, Manfred K. Warmuth, Daniel Hsu (167):1−46, 2022 PDF BibTeX

• A Worst Case Analysis of Calibrated Label Ranking Multi-label Classification Method

  Lucas Henrique Sousa Mello, Flávio Miguel Varejão, Alexandre Loureiros Rodrigues (168):1−30, 2022 PDF BibTeX

• D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data

  Hai Shu, Zhe Qu, Hongtu Zhu (169):1−64, 2022 codePDF BibTeX

• Scalable and Efficient Hypothesis Testing with Random Forests

  Tim Coleman, Wei Peng, Lucas Mentch (170):1−35, 2022 PDF BibTeX

• Interlocking Backpropagation: Improving depthwise model-parallelism

  Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal (171):1−28, 2022 PDF BibTeX

• Projection-free Distributed Online Learning with Sublinear Communication Complexity

  Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang (172):1−53, 2022 PDF BibTeX

• Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training

  Diego Granziol, Stefan Zohren, Stephen Roberts (173):1−65, 2022 PDF BibTeX

• Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models

  Ali Ghadirzadeh, Petra Poklukar, Karol Arndt, Chelsea Finn, Ville Kyrki, Danica Kragic, Mårten Björkman (174):1−37, 2022 PDF BibTeX

• Improved Generalization Bounds for Adversarially Robust Learning

  Idan Attias, Aryeh Kontorovich, Yishay Mansour (175):1−31, 2022 PDF BibTeX

• Signature Moments to Characterize Laws of Stochastic Processes

  Ilya Chevyrev, Harald Oberhauser (176):1−42, 2022 PDF BibTeX

• Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms

  Ping Ma, Yongkai Chen, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael W. Mahoney (177):1−45, 2022 PDF BibTeX

• Logarithmic Regret for Episodic Continuous-Time Linear-Quadratic Reinforcement Learning over a Finite-Time Horizon

  Matteo Basei, Xin Guo, Anran Hu, Yufei Zhang (178):1−34, 2022 PDF BibTeX

• KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints

  Aurélien Garivier, Hédi Hadiji, Pierre Ménard, Gilles Stoltz (179):1−66, 2022 PDF BibTeX

• Matrix Completion with Covariate Information and Informative Missingness

  Huaqing Jin, Yanyuan Ma, Fei Jiang (180):1−62, 2022 codePDF BibTeX

• Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent

  David Holzmüller, Ingo Steinwart (181):1−82, 2022 codePDF BibTeX

• Extensions to the Proximal Distance Method of Constrained Optimization

  Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange (182):1−45, 2022 codePDF BibTeX

• Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution

  Yichen Zhou, Giles Hooker (183):1−44, 2022 codePDF BibTeX

• Statistical Optimality and Stability of Tangent Transform Algorithms in Logit Models

  Indrajit Ghosh, Anirban Bhattacharya, Debdeep Pati (184):1−42, 2022 PDF BibTeX

• A Primer for Neural Arithmetic Logic Modules

  Bhumika Mistry, Katayoun Farrahi, Jonathon Hare (185):1−58, 2022 codePDF BibTeX

• Estimating Density Models with Truncation Boundaries using Score Matching

  Song Liu, Takafumi Kanamori, Daniel J. Williams (186):1−38, 2022 codePDF BibTeX

• Adversarial Classification: Necessary Conditions and Geometric Flows

  Nicolás García Trillos, Ryan Murray (187):1−38, 2022 PDF BibTeX

• Active Structure Learning of Bayesian Networks in an Observational Setting

  Noa Ben-David, Sivan Sabato (188):1−38, 2022 codePDF BibTeX

• Learning to Optimize: A Primer and A Benchmark

  Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin (189):1−59, 2022 codePDF BibTeX

• Clustering with Semidefinite Programming and Fixed Point Iteration

  Pedro Felzenszwalb, Caroline Klivans, Alice Paul (190):1−23, 2022 PDF BibTeX

• Deep Limits and a Cut-Off Phenomenon for Neural Networks

  Benny Avelin, Anders Karlsson (191):1−29, 2022 PDF BibTeX

• A Bregman Learning Framework for Sparse Neural Networks

  Leon Bungert, Tim Roith, Daniel Tenbrinck, Martin Burger (192):1−43, 2022 codePDF BibTeX

• Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression

  Wenjia Wang, Bing-Yi Jing (193):1−67, 2022 PDF BibTeX

• Uniform deconvolution for Poisson Point Processes

  Anna Bonnet, Claire Lacour, Franck Picard, Vincent Rivoirard (194):1−36, 2022 PDF BibTeX

• Distributed Bootstrap for Simultaneous Inference Under High Dimensionality

  Yang Yu, Shih-Kang Chao, Guang Cheng (195):1−77, 2022 codePDF BibTeX

• Universal Approximation Theorems for Differentiable Geometric Deep Learning

  Anastasis Kratsios, Léonie Papon (196):1−73, 2022 PDF BibTeX

• InterpretDL: Explaining Deep Models in PaddlePaddle

  Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Zeyu Chen, Dejing Dou (197):1−6, 2022 codePDF BibTeX

• Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions

  Subha Maity, Yuekai Sun, Moulinath Banerjee (198):1−50, 2022 codePDF BibTeX

• A Forward Approach for Sufficient Dimension Reduction in Binary Classification

  Jongkyeong Kang, Seung Jun Shin (199):1−31, 2022 PDF BibTeX

• A Nonconvex Framework for Structured Dynamic Covariance Recovery

  Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo (200):1−91, 2022 codePDF BibTeX

• Three rates of convergence or separation via U-statistics in a dependent framework

  Quentin Duchemin, Yohann De Castro, Claire Lacour (201):1−59, 2022 codePDF BibTeX

• abess: A Fast Best-Subset Selection Library in Python and R

  Jin Zhu, Xueqin Wang, Liyuan Hu, Junhao Huang, Kangkang Jiang, Yanhang Zhang, Shiyun Lin, Junxian Zhu (202):1−7, 2022 codePDF BibTeX

• Testing Whether a Learning Procedure is Calibrated

  Jon Cockayne, Matthew M. Graham, Chris J. Oates, T. J. Sullivan, Onur Teymur (203):1−36, 2022 PDF BibTeX

• Selective Machine Learning of the Average Treatment Effect with an Invalid Instrumental Variable

  Baoluo Sun, Yifan Cui, Eric Tchetgen Tchetgen (204):1−40, 2022 PDF BibTeX

• Contraction rates for sparse variational approximations in Gaussian process regression

  Dennis Nieman, Botond Szabo, Harry van Zanten (205):1−26, 2022 PDF BibTeX

• Stochastic DCA with Variance Reduction and Applications in Machine Learning

  Hoai An Le Thi, Hoang Phuc Hau Luu, Hoai Minh Le, Tao Pham Dinh (206):1−44, 2022 PDF BibTeX

• Nonconvex Matrix Completion with Linearly Parameterized Factors

  Ji Chen, Xiaodong Li, Zongming Ma (207):1−35, 2022 PDF BibTeX

• tntorch: Tensor Network Learning with PyTorch

  Mikhail Usvyatsov, Rafael Ballester-Ripoll, Konrad Schindler (208):1−6, 2022 codePDF BibTeX

• Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs

  Kaichao You, Yong Liu, Ziyang Zhang, Jianmin Wang, Michael I. Jordan, Mingsheng Long (209):1−47, 2022 codePDF BibTeX

• A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review

  Michael Pearce, Elena A. Erosheva (210):1−33, 2022 PDF BibTeX

• Efficient Inference for Dynamic Flexible Interactions of Neural Populations

  Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu (211):1−49, 2022 PDF BibTeX

• Multi-Agent Multi-Armed Bandits with Limited Communication

  Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli (212):1−24, 2022 PDF BibTeX

• Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features

  Lars H. B. Olsen, Ingrid K. Glad, Martin Jullum, Kjersti Aas (213):1−51, 2022 codePDF BibTeX

• When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint

  Yoav Freund, Yi-An Ma, Tong Zhang (214):1−32, 2022 PDF BibTeX

• Learning Operators with Coupled Attention

  Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris (215):1−63, 2022 PDF BibTeX

• Kernel Partial Correlation Coefficient --- a Measure of Conditional Dependence

  Zhen Huang, Nabarun Deb, Bodhisattva Sen (216):1−58, 2022 PDF BibTeX

• Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee

  Bo Shen, Weijun Xie, Zhenyu (James) Kong (217):1−40, 2022 codePDF BibTeX

• Learning Green's functions associated with time-dependent partial differential equations

  Nicolas Boullé, Seick Kim, Tianyi Shi, Alex Townsend (218):1−34, 2022 PDF BibTeX

• Structural Agnostic Modeling: Adversarial Learning of Causal Graphs

  Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon, David Lopez-Paz, Michèle Sebag (219):1−62, 2022 codePDF BibTeX

• Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks

  Alireza Fallah, Mert Gürbüzbalaban, Asuman Ozdaglar, Umut Şimşekli, Lingjiong Zhu (220):1−96, 2022 PDF BibTeX

• Behavior Priors for Efficient Reinforcement Learning

  Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess (221):1−68, 2022 PDF BibTeX

• Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization

  Huan Li, Zhouchen Lin, Yongchun Fang (222):1−41, 2022 PDF BibTeX

• On Acceleration for Convex Composite Minimization with Noise-Corrupted Gradients and Approximate Proximal Mapping

  Qiang Zhou, Sinno Jialin Pan (223):1−59, 2022 PDF BibTeX

• Getting Better from Worse: Augmented Bagging and A Cautionary Tale of Variable Importance

  Lucas Mentch, Siyu Zhou (224):1−32, 2022 PDF BibTeX

• Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions

  Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh (225):1−48, 2022 PDF BibTeX

• Underspecification Presents Challenges for Credibility in Modern Machine Learning

  Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley (226):1−61, 2022 PDF BibTeX

• Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits

  Hao Chen, Lili Zheng, Raed Al Kontar, Garvesh Raskutti (227):1−59, 2022 PDF BibTeX

• Asymptotic Study of Stochastic Adaptive Algorithms in Non-convex Landscape

  Sébastien Gadat, Ioana Gavra (228):1−54, 2022 PDF BibTeX

• Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration

  Congliang Chen, Li Shen, Fangyu Zou, Wei Liu (229):1−47, 2022 PDF BibTeX

• Multi-Task Dynamical Systems

  Alex Bird, Christopher K. I. Williams, Christopher Hawthorne (230):1−52, 2022 PDF BibTeX

• Representation Learning for Maximization of MI, Nonlinear ICA and Nonlinear Subspaces with Robust Density Ratio Estimation

  Hiroaki Sasaki, Takashi Takenouchi (231):1−55, 2022 PDF BibTeX

• Gaussian Process Boosting

  Fabio Sigrist (232):1−46, 2022 codePDF BibTeX

• An Efficient Sampling Algorithm for Non-smooth Composite Potentials

  Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett (233):1−50, 2022 PDF BibTeX

• Change point localization in dependent dynamic nonparametric random dot product graphs

  Oscar Hernan Madrid Padilla, Yi Yu, Carey E. Priebe (234):1−59, 2022 PDF BibTeX

• Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets

  Arnak S. Dalalyan, Avetik Karagulyan, Lionel Riou-Durand (235):1−38, 2022 PDF BibTeX

• KoPA: Automated Kronecker Product Approximation

  Chencheng Cai, Rong Chen, Han Xiao (236):1−44, 2022 PDF BibTeX

• Nonparametric Principal Subspace Regression

  Yang Zhou, Mark Koudstaal, Dengdeng Yu, Dehan Kong, Fang Yao (237):1−28, 2022 PDF BibTeX

• A Wasserstein Distance Approach for Concentration of Empirical Risk Estimates

  Prashanth L.A., Sanjay P. Bhat (238):1−61, 2022 PDF BibTeX

• Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization

  Zhize Li, Jian Li (239):1−61, 2022 PDF BibTeX

• MALTS: Matching After Learning to Stretch

  Harsh Parikh, Cynthia Rudin, Alexander Volfovsky (240):1−42, 2022 codePDF BibTeX

• Weakly Supervised Disentangled Generative Causal Representation Learning

  Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang (241):1−55, 2022 codePDF BibTeX

• Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure

  Yang Ni, Francesco C. Stingo, Veerabhadran Baladandayuthapani (242):1−29, 2022 PDF BibTeX

• Tree-based Node Aggregation in Sparse Graphical Models

  Ines Wilms, Jacob Bien (243):1−36, 2022 codePDF BibTeX

• Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables

  Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez (244):1−54, 2022 PDF BibTeX

• Mappings for Marginal Probabilities with Applications to Models in Statistical Physics

  Mehdi Molkaraie (245):1−36, 2022 PDF BibTeX

• Multivariate Boosted Trees and Applications to Forecasting and Control

  Lorenzo Nespoli, Vasco Medici (246):1−47, 2022 codePDF BibTeX

• Quantile regression with ReLU Networks: Estimators and minimax rates

  Oscar Hernan Madrid Padilla, Wesley Tansey, Yanzhen Chen (247):1−42, 2022 codePDF BibTeX

• Double Spike Dirichlet Priors for Structured Weighting

  Huiming Lin, Meng Li (248):1−28, 2022 codePDF BibTeX

• Projected Robust PCA with Application to Smooth Image Recovery

  Long Feng, Junhui Wang (249):1−41, 2022 PDF BibTeX

• Non-asymptotic Properties of Individualized Treatment Rules from Sequentially Rule-Adaptive Trials

  Daiqi Gao, Yufeng Liu, Donglin Zeng (250):1−42, 2022 PDF BibTeX

• Using Active Queries to Infer Symmetric Node Functions of Graph Dynamical Systems

  Abhijin Adiga, Chris J. Kuhlman, Madhav V. Marathe, S. S. Ravi, Daniel J. Rosenkrantz, Richard E. Stearns (251):1−43, 2022 PDF BibTeX

• A Closer Look at Embedding Propagation for Manifold Smoothing

  Diego Velazquez, Pau Rodriguez, Josep M. Gonfaus, F. Xavier Roca, Jordi Gonzalez (252):1−27, 2022 PDF BibTeX

• Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences

  Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White (253):1−79, 2022 PDF BibTeX

• Adaptive Greedy Algorithm for Moderately Large Dimensions in Kernel Conditional Density Estimation

  Minh-Lien Jeanne Nguyen, Claire Lacour, Vincent Rivoirard (254):1−74, 2022 PDF BibTeX

• Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States

  Shi Dong, Benjamin Van Roy, Zhengyuan Zhou (255):1−54, 2022 PDF BibTeX

• On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems

  Michael Muehlebach, Michael I. Jordan (256):1−47, 2022 codePDF BibTeX

• Sparse Continuous Distributions and Fenchel-Young Losses

  André F. T. Martins, Marcos Treviso, António Farinhas, Pedro M. Q. Aguiar, Mário A. T. Figueiredo, Mathieu Blondel, Vlad Niculae (257):1−74, 2022 codePDF BibTeX

• Tree-Based Models for Correlated Data

  Assaf Rabinowicz, Saharon Rosset (258):1−31, 2022 PDF BibTeX

• Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models

  Shiwei Lan (259):1−53, 2022 codePDF BibTeX

• A proof of convergence for the gradient descent optimization method with random initializations in the training of neural networks with ReLU activation for piecewise linear target functions

  Arnulf Jentzen, Adrian Riekert (260):1−50, 2022 PDF BibTeX

• Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

  Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter (261):1−61, 2022 codePDF BibTeX

• Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score

  Muxuan Liang, Young-Geun Choi, Yang Ning, Maureen A Smith, Ying-Qi Zhao (262):1−65, 2022 codePDF BibTeX

• The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks

  Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett (263):1−48, 2022 PDF BibTeX

• A Random Matrix Perspective on Random Tensors

  José Henrique de M. Goulart, Romain Couillet, Pierre Comon (264):1−36, 2022 PDF BibTeX

• Stochastic subgradient for composite convex optimization with functional constraints

  Ion Necoara, Nitesh Kumar Singh (265):1−35, 2022 PDF BibTeX

• Functional Linear Regression with Mixed Predictors

  Daren Wang, Zifeng Zhao, Yi Yu, Rebecca Willett (266):1−94, 2022 codePDF BibTeX

• Tianshou: A Highly Modularized Deep Reinforcement Learning Library

  Jiayi Weng, Huayu Chen, Dong Yan, Kaichao You, Alexis Duburcq, Minghao Zhang, Yi Su, Hang Su, Jun Zhu (267):1−6, 2022 codePDF BibTeX

• A Computationally Efficient Framework for Vector Representation of Persistence Diagrams

  Kit C Chan, Umar Islambekov, Alexey Luchinsky, Rebecca Sanders (268):1−33, 2022 PDF BibTeX

• Learning linear non-Gaussian directed acyclic graph with diverging number of nodes

  Ruixuan Zhao, Xin He, Junhui Wang (269):1−34, 2022 PDF BibTeX

• Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling

  Keru Wu, Scott Schmidler, Yuansi Chen (270):1−63, 2022 PDF BibTeX

• Fast Stagewise Sparse Factor Regression

  Kun Chen, Ruipeng Dong, Wanwan Xu, Zemin Zheng (271):1−45, 2022 PDF BibTeX

• Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees

  Kean Ming Tan, Heather Battey, Wen-Xin Zhou (272):1−61, 2022 PDF BibTeX

• The Weighted Generalised Covariance Measure

  Cyrill Scheidegger, Julia Hörrmann, Peter Bühlmann (273):1−68, 2022 PDF BibTeX

• CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms

  Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, João G.M. Araújo (274):1−18, 2022 codePDF BibTeX

• Policy Gradient and Actor-Critic Learning in Continuous Time and Space: Theory and Algorithms

  Yanwei Jia, Xun Yu Zhou (275):1−50, 2022 codePDF BibTeX

• Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons

  Shijun Zhang, Zuowei Shen, Haizhao Yang (276):1−60, 2022 PDF BibTeX

• Nonstochastic Bandits with Composite Anonymous Feedback

  Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Claudio Gentile, Yishay Mansour (277):1−24, 2022 PDF BibTeX

• Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions

  Chiwoo Park (278):1−37, 2022 codePDF BibTeX

• Convergence Guarantees for the Good-Turing Estimator

  Amichai Painsky (279):1−37, 2022 PDF BibTeX

• Generalized Resubstitution for Classification Error Estimation

  Parisa Ghane, Ulisses Braga-Neto (280):1−30, 2022 PDF BibTeX

• Nonparametric adaptive control and prediction: theory and randomized algorithms

  Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine (281):1−46, 2022 PDF BibTeX

• On the Convergence Rates of Policy Gradient Methods

  Lin Xiao (282):1−36, 2022 PDF BibTeX

• De-Sequentialized Monte Carlo: a parallel-in-time particle smoother

  Adrien Corenflos, Nicolas Chopin, Simo Särkkä (283):1−39, 2022 codePDF BibTeX

• Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation

  Chuyang Ke, Jean Honorio (284):1−28, 2022 PDF BibTeX

• Deepchecks: A Library for Testing and Validating Machine Learning Models and Data

  Shir Chorev, Philip Tannor, Dan Ben Israel, Noam Bressler, Itay Gabbay, Nir Hutnik, Jonatan Liberman, Matan Perlmutter, Yurii Romanyshyn, Lior Rokach (285):1−6, 2022 codePDF BibTeX

• Integral Autoencoder Network for Discretization-Invariant Learning

  Yong Zheng Ong, Zuowei Shen, Haizhao Yang (286):1−45, 2022 codePDF BibTeX

• Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning

  Haiyun He, Hanshu Yan, Vincent Y. F. Tan (287):1−52, 2022 codePDF BibTeX

• ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models

  Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim, Miguel D. Mahecha, Karin Mora (288):1−8, 2022 codePDF BibTeX

• Estimating Causal Effects under Network Interference with Bayesian Generalized Propensity Scores

  Laura Forastiere, Fabrizia Mealli, Albert Wu, Edoardo M. Airoldi (289):1−61, 2022 PDF BibTeX

• Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data

  Davoud Ataee Tarzanagh, George Michailidis (290):1−49, 2022 codePDF BibTeX

• Generalized Matrix Factorization: efficient algorithms for fitting generalized linear latent variable models to large data arrays

  Lukasz Kidzinski, Francis K.C. Hui, David I. Warton, Trevor J. Hastie (291):1−29, 2022 codePDF BibTeX

• Two-mode Networks: Inference with as Many Parameters as Actors and Differential Privacy

  Qiuping Wang, Ting Yan, Binyan Jiang, Chenlei Leng (292):1−38, 2022 PDF BibTeX

• Expected Regret and Pseudo-Regret are Equivalent When the Optimal Arm is Unique

  Daron Anderson, Douglas J. Leith (293):1−12, 2022 PDF BibTeX

• Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

  Bernardo Fichera, Aude Billard (294):1−35, 2022 PDF BibTeX

• Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables

  Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser (295):1−76, 2022 codePDF BibTeX

• Stable Classification

  Dimitris Bertsimas, Jack Dunn, Ivan Paskov (296):1−53, 2022 PDF BibTeX

• Handling Hard Affine SDP Shape Constraints in RKHSs

  Pierre-Cyril Aubin-Frankowski, Zoltan Szabo (297):1−54, 2022 codePDF BibTeX

• JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data

  Šimon Mandlík, Matěj Račinský, Viliam Lisý, Tomáš Pevný (298):1−5, 2022 codePDF BibTeX

• Interpretable Classification of Categorical Time Series Using the Spectral Envelope and Optimal Scalings

  Zeda Li, Scott A. Bruce, Tian Cai (299):1−31, 2022 codePDF BibTeX

• More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming

  Vo Nguyen Le Duy, Ichiro Takeuchi (300):1−37, 2022 codePDF BibTeX

• Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data

  T. Tony Cai, Rong Ma (301):1−54, 2022 PDF BibTeX

• On Instrumental Variable Regression for Deep Offline Policy Evaluation

  Yutian Chen, Liyuan Xu, Caglar Gulcehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet (302):1−40, 2022 codePDF BibTeX

• Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks

  Alice Gatti, Zhixiong Hu, Tess Smidt, Esmond G. Ng, Pieter Ghysels (303):1−28, 2022 codePDF BibTeX

• Variational Inference in high-dimensional linear regression

  Sumit Mukherjee, Subhabrata Sen (304):1−56, 2022 PDF BibTeX

• Tree-Values: Selective Inference for Regression Trees

  Anna C. Neufeld, Lucy L. Gao, Daniela M. Witten (305):1−43, 2022 codePDF BibTeX

• Pathfinder: Parallel quasi-Newton variational inference

  Lu Zhang, Bob Carpenter, Andrew Gelman, Aki Vehtari (306):1−49, 2022 codePDF BibTeX

• Learning from Noisy Pairwise Similarity and Unlabeled Data

  Songhua Wu, Tongliang Liu, Bo Han, Jun Yu, Gang Niu, Masashi Sugiyama (307):1−34, 2022 codePDF BibTeX

• On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations

  Hong T.M. Chu, Kim-Chuan Toh, Yangjing Zhang (308):1−39, 2022 PDF BibTeX

• The Separation Capacity of Random Neural Networks

  Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk (309):1−47, 2022 PDF BibTeX

• Detecting Latent Communities in Network Formation Models

  Shujie Ma, Liangjun Su, Yichong Zhang (310):1−61, 2022 PDF BibTeX

• Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective

  Tenghui Li, Guoxu Zhou, Yuning Qiu, Qibin Zhao (311):1−50, 2022 codePDF BibTeX

• Nystrom Regularization for Time Series Forecasting

  Zirui Sun, Mingwei Dai, Yao Wang, Shao-Bo Lin (312):1−42, 2022 PDF BibTeX

• Intrinsic Dimension Estimation Using Wasserstein Distance

  Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin (313):1−37, 2022 PDF BibTeX

• Oracle Complexity in Nonsmooth Nonconvex Optimization

  Guy Kornowski, Ohad Shamir (314):1−44, 2022 PDF BibTeX

• d3rlpy: An Offline Deep Reinforcement Learning Library

  Takuma Seno, Michita Imai (315):1−20, 2022 codePDF BibTeX

• WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

  Tian Lan, Sunil Srinivasa, Huan Wang, Stephan Zheng (316):1−6, 2022 codePDF BibTeX

• Nonparametric Neighborhood Selection in Graphical Models

  Hao Dong, Yuedong Wang (317):1−36, 2022 PDF BibTeX

• Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth

  Jeff Calder, Mahmood Ettehad (318):1−62, 2022 codePDF BibTeX

• Self-Healing Robust Neural Networks via Closed-Loop Control

  Zhuotong Chen, Qianxiao Li, Zheng Zhang (319):1−54, 2022 codePDF BibTeX

• Network Regression with Graph Laplacians

  Yidong Zhou, Hans-Georg Müller (320):1−41, 2022 codePDF BibTeX

• On Low-rank Trace Regression under General Sampling Distribution

  Nima Hamidi, Mohsen Bayati (321):1−49, 2022 codePDF BibTeX

• Community detection in sparse latent space models

  Fengnan Gao, Zongming Ma, Hongsong Yuan (322):1−50, 2022 PDF BibTeX

• Convergence Rates for Gaussian Mixtures of Experts

  Nhat Ho, Chiao-Yu Yang, Michael I. Jordan (323):1−81, 2022 PDF BibTeX

• Improving Bayesian Network Structure Learning in the Presence of Measurement Error

  Yang Liu, Anthony C. Constantinou, Zhigao Guo (324):1−28, 2022 codePDF BibTeX

• On Mixup Regularization

  Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert (325):1−31, 2022 PDF BibTeX

• Project and Forget: Solving Large-Scale Metric Constrained Problems

  Rishi Sonthalia, Anna C. Gilbert (326):1−54, 2022 codePDF BibTeX

• Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence

  Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai (327):1−34, 2022 PDF BibTeX

• Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima

  Brian Swenson, Ryan Murray, H. Vincent Poor, Soummya Kar (328):1−62, 2022 PDF BibTeX

• Joint Continuous and Discrete Model Selection via Submodularity

  Jonathan Bunton, Paulo Tabuada (329):1−42, 2022 PDF BibTeX

• ALMA: Alternating Minimization Algorithm for Clustering Mixture Multilayer Network

  Xing Fan, Marianna Pensky, Feng Yu, Teng Zhang (330):1−46, 2022 PDF BibTeX

• The Geometry of Uniqueness, Sparsity and Clustering in Penalized Estimation

  Ulrike Schneider, Patrick Tardivel (331):1−36, 2022 PDF BibTeX

• Maximum sampled conditional likelihood for informative subsampling

  HaiYing Wang, Jae Kwang Kim (332):1−50, 2022 PDF BibTeX

• Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression

  Domagoj Cevid, Loris Michel, Jeffrey Näf, Peter Bühlmann, Nicolai Meinshausen (333):1−79, 2022 PDF BibTeX

• Fully General Online Imitation Learning

  Michael K. Cohen, Marcus Hutter, Neel Nanda (334):1−30, 2022 PDF BibTeX

• Causal Aggregation: Estimation and Inference of Causal Effects by Constraint-Based Data Fusion

  Jaime Roquero Gimenez, Dominik Rothenhäusler (335):1−60, 2022 PDF BibTeX

• Faster Randomized Interior Point Methods for Tall/Wide Linear Programs

  Agniva Chowdhury, Gregory Dexter, Palma London, Haim Avron, Petros Drineas (336):1−48, 2022 PDF BibTeX

• Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA

  Nicholas Sterge, Bharath K. Sriperumbudur (337):1−32, 2022 PDF BibTeX

• Interval-censored Hawkes processes

  Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Pio Calderon, Leanne J. Dong, Aditya Krishna Menon, Lexing Xie (338):1−84, 2022 PDF BibTeX

• Early Stopping for Iterative Regularization with General Loss Functions

  Ting Hu, Yunwen Lei (339):1−36, 2022 PDF BibTeX

• Fundamental Limits and Tradeoffs in Invariant Representation Learning

  Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar (340):1−49, 2022 PDF BibTeX

• Information-theoretic Classification Accuracy: A Criterion that Guides Data-driven Combination of Ambiguous Outcome Labels in Multi-class Classification

  Chihao Zhang, Yiling Elaine Chen, Shihua Zhang, Jingyi Jessica Li (341):1−65, 2022 codePDF BibTeX

• SGD with Coordinate Sampling: Theory and Practice

  Rémi Leluc, François Portier (342):1−47, 2022 codePDF BibTeX

• Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch

  Shangtong Zhang, Remi Tachet des Combes, Romain Laroche (343):1−91, 2022 codePDF BibTeX

• Vector-Valued Least-Squares Regression under Output Regularity Assumptions

  Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc (344):1−50, 2022 PDF BibTeX

• Constraint Reasoning Embedded Structured Prediction

  Nan Jiang, Maosen Zhang, Willem-Jan van Hoeve, Yexiang Xue (345):1−40, 2022 codePDF BibTeX

• Minimax optimal approaches to the label shift problem in non-parametric settings

  Subha Maity, Yuekai Sun, Moulinath Banerjee (346):1−45, 2022 PDF BibTeX

• Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks

  El Mehdi Achour, François Malgouyres, Franck Mamalet (347):1−56, 2022 codePDF BibTeX

• Scalable Gaussian-process regression and variable selection using Vecchia approximations

  Jian Cao, Joseph Guinness, Marc G. Genton, Matthias Katzfuss (348):1−30, 2022 codePDF BibTeX

• OMLT: Optimization & Machine Learning Toolkit

  Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D Laird, Ruth Misener (349):1−8, 2022 codePDF BibTeX

• Approximate Bayesian Computation via Classification

  Yuexi Wang, Tetsuya Kaji, Veronika Rockova (350):1−49, 2022 PDF BibTeX

• Metrics of Calibration for Probabilistic Predictions

  Imanol Arrieta-Ibarra, Paman Gujral, Jonathan Tannen, Mark Tygert, Cherie Xu (351):1−54, 2022 codePDF BibTeX