Journal of Machine Learning Research

The Journal of Machine Learning Research (JMLR), established in 2000, provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online.

News

• 2023.01.20: Volume 23 completed; Volume 24 began.
• 2022.07.20: New special issue on climate change.
• 2022.02.18: New blog post: Retrospectives from 20 Years of JMLR .
• 2022.01.25: Volume 22 completed; Volume 23 began.
• 2021.12.02: Message from outgoing co-EiC Bernhard Schölkopf.
• 2021.02.10: Volume 21 completed; Volume 22 began.
• More news ...

Latest papers

• From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions

  Johannes Resin, 2023

• Beyond the Golden Ratio for Variational Inequality Algorithms

  Ahmet Alacaoglu, Axel Böhm, Yura Malitsky, 2023

• Incremental Learning in Diagonal Linear Networks

  Raphaël Berthier, 2023

• Small Transformers Compute Universal Metric Embeddings

  Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić, 2023

• DART: Distance Assisted Recursive Testing

  Xuechan Li, Anthony D. Sung, Jichun Xie, 2023

• Inference on the Change Point under a High Dimensional Covariance Shift

  Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis, George Michailidis, 2023

• Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start

  Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, 2023

• A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition

  Masaru Ito, Zhaosong Lu, Chuan He, 2023

• Robust Methods for High-Dimensional Linear Learning

  Ibrahim Merad, Stéphane Gaïffas, 2023

• A Framework and Benchmark for Deep Batch Active Learning for Regression

  David Holzmüller, Viktor Zaverkin, Johannes Kästner, Ingo Steinwart, 2023

• Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification

  Gavin Zhang, Salar Fattahi, Richard Y. Zhang, 2023

• Flexible Model Aggregation for Quantile Regression

  Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani, 2023

• q-Learning in Continuous Time

  Yanwei Jia, Xun Yu Zhou, 2023

• Multivariate Soft Rank via Entropy-Regularized Optimal Transport: Sample Efficiency and Generative Modeling

  Shoaib Bin Masud, Matthew Werenski, James M. Murphy, Shuchin Aeron, 2023

• Infinite-dimensional optimization and Bayesian nonparametric learning of stochastic differential equations

  Arnab Ganguly, Riten Mitra, Jinpu Zhou, 2023

• Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees

  Hamid Reza Feyzmahdavian, Mikael Johansson, 2023

• Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the in the O(epsilon^(-7/4)) Complexity

  Huan Li, Zhouchen Lin, 2023

• Integrating Random Effects in Deep Neural Networks

  Giora Simchoni, Saharon Rosset, 2023

• Adaptive Data Depth via Multi-Armed Bandits

  Tavor Baharav, Tze Leung Lai, 2023

• Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees

  Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd, 2023

• Consistent Model-based Clustering using the Quasi-Bernoulli Stick-breaking Process

  Cheng Zeng, Jeffrey W Miller, Leo L Duan, 2023

• Selective inference for k-means clustering

  Yiqun T. Chen, Daniela M. Witten, 2023

• Generalization error bounds for multiclass sparse linear classifiers

  Tomer Levy, Felix Abramovich, 2023

• MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning

  Ming Zhou, Ziyu Wan, Hanjing Wang, Muning Wen, Runzhe Wu, Ying Wen, Yaodong Yang, Yong Yu, Jun Wang, Weinan Zhang, 2023

• Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning

  Titouan Vayer, Rémi Gribonval, 2023

• Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition

  Zhishuai Guo, Yan Yan, Zhuoning Yuan, Tianbao Yang, 2023

• Stochastic Optimization under Distributional Drift

  Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui, 2023

• Off-Policy Actor-Critic with Emphatic Weightings

  Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White, 2023

• Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning

  Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang, 2023

• Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering

  Noirrit Kiran Chandra, Antonio Canale, David B. Dunson, 2023

• Large sample spectral analysis of graph-based multi-manifold clustering

  Nicolas Garcia Trillos, Pengfei He, Chenghui Li, 2023

• On Tilted Losses in Machine Learning: Theory and Applications

  Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith, 2023

• Optimal Convergence Rates for Distributed Nystroem Approximation

  Jian Li, Yong Liu, Weiping Wang, 2023

• Jump Interval-Learning for Individualized Decision Making with Continuous Treatments

  Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu, 2023

• Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games

  Ben Hambly, Renyuan Xu, Huining Yang, 2023

• Asymptotics of Network Embeddings Learned via Subsampling

  Andrew Davison, Morgane Austern, 2023

• Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks

  Hui Jin, Guido Montufar, 2023

• Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection

  Wenhao Li, Ningyuan Chen, L. Jeff Hong, 2023

• Sparse GCA and Thresholded Gradient Descent

  Sheng Gao, Zongming Ma, 2023

• MARS: A Second-Order Reduction Algorithm for High-Dimensional Sparse Precision Matrices Estimation

  Qian Li, Binyan Jiang, Defeng Sun, 2023

• Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

  Benjamin Jakubowski, Sriram Somanchi, Edward McFowland III, Daniel B. Neill, 2023

• Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data

  Di Wang, Lijie Hu, Huanyu Zhang, Marco Gaboardi, Jinhui Xu, 2023

• A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition

  Patricia Wollstadt, Sebastian Schmitt, Michael Wibral, 2023

• Combinatorial Optimization and Reasoning with Graph Neural Networks

  Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic, 2023

• A First Look into the Carbon Footprint of Federated Learning

  Xinchi Qiu, Titouan Parcollet, Javier Fernandez-Marques, Pedro P. B. Gusmao, Yan Gao, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane, 2023

• An Eigenmodel for Dynamic Multilayer Networks

  Joshua Daniel Loyal, Yuguo Chen, 2023

• Graph Clustering with Graph Neural Networks

  Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller, 2023

• Euler-Lagrange Analysis of Generative Adversarial Networks

  Siddarth Asokan, Chandra Sekhar Seelamantula, 2023

• Statistical Robustness of Empirical Risks in Machine Learning

  Shaoyan Guo, Huifu Xu, Liwei Zhang, 2023

• HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation

  Weijie J. Su, Yuancheng Zhu, 2023

• Benign overfitting in ridge regression

  Alexander Tsigler, Peter L. Bartlett, 2023

• Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities

  Brian R. Bartoldson, Bhavya Kailkhura, Davis Blalock, 2023

• Minimal Width for Universal Property of Deep RNN

  Chang hoon Song, Geonho Hwang, Jun ho Lee, Myungjoo Kang, 2023

• Maximum likelihood estimation in Gaussian process regression is ill-posed

  Toni Karvonen, Chris J. Oates, 2023

• An Annotated Graph Model with Differential Degree Heterogeneity for Directed Networks

  Stefan Stein, Chenlei Leng, 2023

• A Unified Framework for Optimization-Based Graph Coarsening

  Manoj Kumar, Anurag Sharma, Sandeep Kumar, 2023

• Deep linear networks can benignly overfit when shallow ones do

  Niladri S. Chatterji, Philip M. Long, 2023

• SQLFlow: An Extensible Toolkit Integrating DB and AI

  Jun Zhou, Ke Zhang, Lin Wang, Hua Wu, Yi Wang, ChaoChao Chen, 2023

• Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition

  Chengzhuo Ni, Yaqi Duan, Munther Dahleh, Mengdi Wang, Anru R. Zhang, 2023

• Generalization Bounds for Adversarial Contrastive Learning

  Xin Zou, Weiwei Liu, 2023

• The Implicit Bias of Benign Overfitting

  Ohad Shamir, 2023

• The Hyperspherical Geometry of Community Detection: Modularity as a Distance

  Martijn Gösgens, Remco van der Hofstad, Nelly Litvak, 2023

• FLIP: A Utility Preserving Privacy Mechanism for Time Series

  Tucker McElroy, Anindya Roy, Gaurab Hore, 2023

• A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates

  Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi, 2023

• Dimensionless machine learning: Imposing exact units equivariance

  Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu, 2023

• Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors

  Michail Spitieris, Ingelin Steinsland, 2023

• Risk Bounds for Positive-Unlabeled Learning Under the Selected At Random Assumption

  Olivier Coudray, Christine Keribin, Pascal Massart, Patrick Pamphile, 2023

• Concentration analysis of multivariate elliptic diffusions

  Lukas Trottner, Cathrine Aeckerle-Willems, Claudia Strauch, 2023

• Knowledge Hypergraph Embedding Meets Relational Algebra

  Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole, 2023

• Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics

  Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang, 2023

• Sparse Training with Lipschitz Continuous Loss Functions and a Weighted Group L0-norm Constraint

  Michael R. Metel, 2023

• Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments

  Haixu Ma, Donglin Zeng, Yufeng Liu, 2023

• Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds

  Didong Li, Wenpin Tang, Sudipto Banerjee, 2023

• FedLab: A Flexible Federated Learning Framework

  Dun Zeng, Siqi Liang, Xiangjing Hu, Hui Wang, Zenglin Xu, 2023

• Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity

  Artem Vysogorets, Julia Kempe, 2023

• An Analysis of Robustness of Non-Lipschitz Networks

  Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang, 2023

• Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation

  Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, Li-Ping Liu, 2023

• Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization

  Jianhao Ma, Salar Fattahi, 2023

• Statistical Inference for Noisy Incomplete Binary Matrix

  Yunxiao Chen, Chengcheng Li, Jing Ouyang, Gongjun Xu, 2023

• Faith-Shap: The Faithful Shapley Interaction Index

  Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar, 2023

• Decentralized Learning: Theoretical Optimality and Practical Improvements

  Yucheng Lu, Christopher De Sa, 2023

• Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption

  Lihu Xu, Fang Yao, Qiuran Yao, Huiming Zhang, 2023

• Recursive Quantile Estimation: Non-Asymptotic Confidence Bounds

  Likai Chen, Georg Keilbar, Wei Biao Wu, 2023

• Outlier-Robust Subsampling Techniques for Persistent Homology

  Bernadette J. Stolz, 2023

• Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs

  Nikola Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar, 2023

• Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data

  Yuqi Gu, Elena E. Erosheva, Gongjun Xu, David B. Dunson, 2023

• Gaussian Processes with Errors in Variables: Theory and Computation

  Shuang Zhou, Debdeep Pati, Tianying Wang, Yun Yang, Raymond J. Carroll, 2023

• Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces

  George Stepaniants, 2023

• Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence

  Henry Lam, Haofeng Zhang, 2023

• Online Optimization over Riemannian Manifolds

  Xi Wang, Zhipeng Tu, Yiguang Hong, Yingyi Wu, Guodong Shi, 2023

• Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees

  William J. Wilkinson, Simo Särkkä, Arno Solin, 2023

• Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality

  Ning Ning, Edward L. Ionides, 2023

• Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics

  Gaetano Romano, Idris A. Eckley, Paul Fearnhead, Guillem Rigaill, 2023

• Temporal Abstraction in Reinforcement Learning with the Successor Representation

  Marlos C. Machado, Andre Barreto, Doina Precup, Michael Bowling, 2023

• Approximate Post-Selective Inference for Regression with the Group LASSO

  Snigdha Panigrahi, Peter W MacDonald, Daniel Kessler, 2023

• Towards Learning to Imitate from a Single Video Demonstration

  Glen Berseth, Florian Golemo, Christopher Pal, 2023

• A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models

  Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin, 2023

• A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection

  Di Bo, Hoon Hwangbo, Vinit Sharma, Corey Arndt, Stephanie TerMaath, 2023

• Intrinsic Persistent Homology via Density-based Metric Learning

  Ximena Fernández, Eugenio Borghini, Gabriel Mindlin, Pablo Groisman, 2023

• Privacy-Aware Rejection Sampling

  Jordan Awan, Vinayak Rao, 2023

• Inference for a Large Directed Acyclic Graph with Unspecified Interventions

  Chunlin Li, Xiaotong Shen, Wei Pan, 2023

• How Do You Want Your Greedy: Simultaneous or Repeated?

  Moran Feldman, Christopher Harshaw, Amin Karbasi, 2023

• Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition

  Simon Bartels, Wouter Boomsma, Jes Frellsen, Damien Garreau, 2023

• Optimizing ROC Curves with a Sort-Based Surrogate Loss for Binary Classification and Changepoint Detection

  Jonathan Hillman, Toby Dylan Hocking, 2023

• When Locally Linear Embedding Hits Boundary

  Hau-Tieng Wu, Nan Wu, 2023

• Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data

  Ruoyu Wang, Miaomiao Su, Qihua Wang, 2023

• Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching

  Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann, Arto Klami, 2023

• Posterior Contraction for Deep Gaussian Process Priors

  Gianluca Finocchio, Johannes Schmidt-Hieber, 2023

• Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule

  Nikhil Iyer, V. Thejas, Nipun Kwatra, Ramachandran Ramjee, Muthian Sivathanu, 2023

• Fundamental limits and algorithms for sparse linear regression with sublinear sparsity

  Lan V. Truong, 2023

• On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results

  Marcelo Arenas, Pablo Barcelo, Leopoldo Bertossi, Mikael Monet, 2023

• Monotonic Alpha-divergence Minimisation for Variational Inference

  Kamélia Daudel, Randal Douc, François Roueff, 2023

• Density estimation on low-dimensional manifolds: an inflation-deflation approach

  Christian Horvat, Jean-Pascal Pfister, 2023

• Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints

  Qinbo Bai, Vaneet Aggarwal, Ather Gattami, 2023

• Topological Convolutional Layers for Deep Learning

  Ephy R. Love, Benjamin Filippenko, Vasileios Maroulas, Gunnar Carlsson, 2023

• Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval

  Yan Shuo Tan, Roman Vershynin, 2023

• Tree-AMP: Compositional Inference with Tree Approximate Message Passing

  Antoine Baker, Florent Krzakala, Benjamin Aubin, Lenka Zdeborová, 2023

• On the geometry of Stein variational gradient descent

  Andrew Duncan, Nikolas Nüsken, Lukasz Szpruch, 2023

• Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches

  Shaogao Lv, Xin He, Junhui Wang, 2023

• Contextual Stochastic Block Model: Sharp Thresholds and Contiguity

  Chen Lu, Subhabrata Sen, 2023

• VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback

  Kirthevasan Kandasamy, Joseph E Gonzalez, Michael I Jordan, Ion Stoica, 2023

• Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

  Kunal Pattanayak, Vikram Krishnamurthy, 2023

• Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks

  Lingjun Li, Jun Li, 2023

• Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning

  Linxi Liu, Dangna Li, Wing Hung Wong, 2023

• Reinforcement Learning for Joint Optimization of Multiple Rewards

  Mridul Agarwal, Vaneet Aggarwal, 2023

• On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size

  Xiaoyu Wang, Ya-xiang Yuan, 2023

• A Group-Theoretic Approach to Computational Abstraction: Symmetry-Driven Hierarchical Clustering

  Haizi Yu, Igor Mineyev, Lav R. Varshney, 2023

• The d-Separation Criterion in Categorical Probability

  Tobias Fritz, Andreas Klingler, 2023

• The multimarginal optimal transport formulation of adversarial multiclass classification

  Nicolás García Trillos, Matt Jacobs, Jakwang Kim, 2023

• Robust Load Balancing with Machine Learned Advice

  Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni, Binghui Peng, 2023

• Benchmarking Graph Neural Networks

  Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson, 2023

• A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

  Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan, 2023

• Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data

  Shaowu Pan, Steven L. Brunton, J. Nathan Kutz, 2023

• On Batch Teaching Without Collusion

  Shaun Fallat, David Kirkpatrick, Hans U. Simon, Abolghasem Soltani, Sandra Zilles, 2023

• Sensing Theorems for Unsupervised Learning in Linear Inverse Problems

  Julián Tachella, Dongdong Chen, Mike Davies, 2023

• First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems

  Michael I. Jordan, Tianyi Lin, Manolis Zampetakis, 2023

• Ridges, Neural Networks, and the Radon Transform

  Michael Unser, 2023

• Label Distribution Changing Learning with Sample Space Expanding

  Chao Xu, Hong Tao, Jing Zhang, Dewen Hu, Chenping Hou, 2023

• Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?

  Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan, 2023

• Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

  Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne, 2023

• Gap Minimization for Knowledge Sharing and Transfer

  Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton, 2023

• Sparse PCA: a Geometric Approach

  Dimitris Bertsimas, Driss Lahlou Kitane, 2023

• Labels, Information, and Computation: Efficient Learning Using Sufficient Labels

  Shiyu Duan, Spencer Chang, Jose C. Principe, 2023

• Attacks against Federated Learning Defense Systems and their Mitigation

  Cody Lewis, Vijay Varadharajan, Nasimul Noman, 2023

• HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn

  Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard, 2023

• Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping

  XuranMeng, JeffYao, 2023

• The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time

  Raj Agrawal, Tamara Broderick, 2023

• Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels

  Hao Wang, Rui Gao, Flavio P. Calmon, 2023

• Discrete Variational Calculus for Accelerated Optimization

  Cédric M. Campos, Alejandro Mahillo, David Martín de Diego, 2023

• Calibrated Multiple-Output Quantile Regression with Representation Learning

  Shai Feldman, Stephen Bates, Yaniv Romano, 2023

• Bayesian Data Selection

  Eli N. Weinstein, Jeffrey W. Miller, 2023

• Lower Bounds and Accelerated Algorithms for Bilevel Optimization

  Kaiyi ji, Yingbin Liang, 2023

• Graph-Aided Online Multi-Kernel Learning

  Pouya M. Ghari, Yanning Shen, 2023

• Interpolating Classifiers Make Few Mistakes

  Tengyuan Liang, Benjamin Recht, 2023

• Regularized Joint Mixture Models

  Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger, Sach Mukherjee, 2023

• An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization

  Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis, 2023

• Learning Mean-Field Games with Discounted and Average Costs

  Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi, 2023

• Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation

  Cynthia Rudin, Yaron Shaposhnik, 2023

• Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions

  Jon Vadillo, Roberto Santana, Jose A. Lozano, 2023

• Python package for causal discovery based on LiNGAM

  Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, Shohei Shimizu, 2023

• Adaptation to the Range in K-Armed Bandits

  Hédi Hadiji, Gilles Stoltz, 2023

• Learning-augmented count-min sketches via Bayesian nonparametrics

  Emanuele Dolera, Stefano Favaro, Stefano Peluchetti, 2023

• Optimal Strategies for Reject Option Classifiers

  Vojtech Franc, Daniel Prusa, Vaclav Voracek, 2023

• A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees

  Michael J. O'Neill, Stephen J. Wright, 2023

• Sampling random graph homomorphisms and applications to network data analysis

  Hanbaek Lyu, Facundo Memoli, David Sivakoff, 2023

• A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs

  Radu I. Bot, Michael Sedlmayer, Phan Tu Vuong, 2023

• On Distance and Kernel Measures of Conditional Dependence

  Tianhong Sheng, Bharath K. Sriperumbudur, 2023

• AutoKeras: An AutoML Library for Deep Learning

  Haifeng Jin, François Chollet, Qingquan Song, Xia Hu, 2023

• Cluster-Specific Predictions with Multi-Task Gaussian Processes

  Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey, 2023

• Efficient Structure-preserving Support Tensor Train Machine

  Kirandeep Kour, Sergey Dolgov, Martin Stoll, Peter Benner, 2023

• Bayesian Spiked Laplacian Graphs

  Leo L Duan, George Michailidis, Mingzhou Ding, 2023

• The Brier Score under Administrative Censoring: Problems and a Solution

  Håvard Kvamme, Ørnulf Borgan, 2023

• Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search

  Benjamin Moseley, Joshua R. Wang, 2023

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