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

• 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

• Inherent Tradeoffs in Learning Fair Representations

  Han Zhao, Geoffrey J. Gordon, 2022

• 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, 2022

• Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy

  Terrance D. Savitsky, Matthew R.Williams, Jingchen Hu, 2022

• 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, 2022

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

  Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler, 2022

• LinCDE: Conditional Density Estimation via Lindsey's Method

  Zijun Gao, Trevor Hastie, 2022

• Toolbox for Multimodal Learn (scikit-multimodallearn)

  Dominique Benielli, Baptiste Bauvin, Sokol Koço, Riikka Huusari, Cécile Capponi, Hachem Kadri, François Laviolette, 2022

• Analytically Tractable Hidden-States Inference in Bayesian Neural Networks

  Luong-Ha Nguyen, James-A. Goulet, 2022

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

  Xinyi Wang, Lang Tong, 2022

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

  Zhiyan Ding, Shi Chen, Qin Li, Stephen J. Wright, 2022

• Cascaded Diffusion Models for High Fidelity Image Generation

  Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans, 2022

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

  Wanrong Zhu, Zhipeng Lou, Wei Biao Wu, 2022

• Optimal Transport for Stationary Markov Chains via Policy Iteration

  Kevin O'Connor, Kevin McGoff, Andrew B. Nobel, 2022

• PAC Guarantees and Effective Algorithms for Detecting Novel Categories

  Si Liu, Risheek Garrepalli, Dan Hendrycks, Alan Fern, Debashis Mondal, Thomas G. Dietterich, 2022

• Sampling Permutations for Shapley Value Estimation

  Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes, 2022

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

  Zhong Li, Jiequn Han, Weinan E, Qianxiao Li, 2022

• The correlation-assisted missing data estimator

  Timothy I. Cannings, Yingying Fan, 2022

• Structure-adaptive Manifold Estimation

  Nikita Puchkin, Vladimir Spokoiny, 2022

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

  Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, Luc Rey-Bellet, 2022

• Score Matched Neural Exponential Families for Likelihood-Free Inference

  Lorenzo Pacchiardi, Ritabrata Dutta, 2022

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

  Matteo Pegoraro, Mario Beraha, 2022

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

  Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang, 2022

• Optimality and Stability in Non-Convex Smooth Games

  Guojun Zhang, Pascal Poupart, Yaoliang Yu, 2022

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

  Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu, 2022

• Model Averaging Is Asymptotically Better Than Model Selection For Prediction

  Tri M. Le, Bertrand S. Clarke, 2022

• Active Learning for Nonlinear System Identification with Guarantees

  Horia Mania, Michael I. Jordan, Benjamin Recht, 2022

• An improper estimator with optimal excess risk in misspecified density estimation and logistic regression

  Jaouad Mourtada, Stéphane Gaïffas, 2022

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

  Augusto Fasano, Daniele Durante, 2022

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

  Kaiyi Ji, Junjie Yang, Yingbin Liang, 2022

• Novel Min-Max Reformulations of Linear Inverse Problems

  Mohammed Rayyan Sheriff, Debasish Chatterjee, 2022

• Data-Derived Weak Universal Consistency

  Narayana Santhanam, Venkatachalam Anantharam, Wojciech Szpankowski, 2022

• 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, 2022

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

  Maxime Vono, Daniel Paulin, Arnaud Doucet, 2022

• On Biased Stochastic Gradient Estimation

  Derek Driggs, Jingwei Liang, Carola-Bibiane Schönlieb, 2022

• Fast and Robust Rank Aggregation against Model Misspecification

  Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama, 2022

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

  Ali Eshragh, Fred Roosta, Asef Nazari, Michael W. Mahoney, 2022

• Evolutionary Variational Optimization of Generative Models

  Jakob Drefs, Enrico Guiraud, Jörg Lücke, 2022

• Supervised Dimensionality Reduction and Visualization using Centroid-Encoder

  Tomojit Ghosh, Michael Kirby, 2022

• Universal Approximation in Dropout Neural Networks

  Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies, Jaron Sanders, Albert Senen-Cerda, 2022

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

  Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang, 2022

• Spatial Multivariate Trees for Big Data Bayesian Regression

  Michele Peruzzi, David B. Dunson, 2022

• 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, 2022

• A Stochastic Bundle Method for Interpolation

  Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel, M. Pawan Kumar, 2022

• On Generalizations of Some Distance Based Classifiers for HDLSS Data

  Sarbojit Roy, Soham Sarkar, Subhajit Dutta, Anil K. Ghosh, 2022

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

  Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet, 2022

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

  Jayakumar Subramanian, Amit Sinha, Raihan Seraj, Aditya Mahajan, 2022

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

  Ali Kara, Serdar Yuksel, 2022

• Interpolating Predictors in High-Dimensional Factor Regression

  Florentina Bunea, Seth Strimas-Mackey, Marten Wegkamp, 2022

• Scaling Laws from the Data Manifold Dimension

  Utkarsh Sharma, Jared Kaplan, 2022

• Deep Learning in Target Space

  Michael Fairbank, Spyridon Samothrakis, Luca Citi, 2022

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

  Justin D. Silverman, Kimberly Roche, Zachary C. Holmes, Lawrence A. David, Sayan Mukherjee, 2022

• XAI Beyond Classification: Interpretable Neural Clustering

  Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, Joey Tianyi Zhou, 2022

• Empirical Risk Minimization under Random Censorship

  Guillaume Ausset, Stephan Clémençon, François Portier, 2022

• Exploiting locality in high-dimensional Factorial hidden Markov models

  Lorenzo Rimella, Nick Whiteley, 2022

• Recovering shared structure from multiple networks with unknown edge distributions

  Keith Levin, Asad Lodhia, Elizaveta Levina, 2022

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

  Shaogao Lv, Heng Lian, 2022

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

  Subhabrata Majumdar, George Michailidis, 2022

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