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Journal of Machine Learning Research

The Journal of Machine Learning Research (JMLR) 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.

JMLR has a commitment to rigorous yet rapid reviewing. Final versions are published electronically (ISSN 1533-7928) immediately upon receipt. Until the end of 2004, paper volumes (ISSN 1532-4435) were published 8 times annually and sold to libraries and individuals by the MIT Press. Paper volumes (ISSN 1532-4435) are now published and sold by Microtome Publishing.


Latest papers

From Low Probability to High Confidence in Stochastic Convex Optimization
Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao, Junyu Zhang, 2021.
[abs][pdf][bib]

Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression
Behzad Azmi, Dante Kalise, Karl Kunisch, 2021.
[abs][pdf][bib]

Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory
Soon Hoe Lim, 2021.
[abs][pdf][bib]

Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates
Tony Cai, Hongzhe Li, Rong Ma, 2021.
[abs][pdf][bib]

RaSE: Random Subspace Ensemble Classification
Ye Tian, Yang Feng, 2021.
[abs][pdf][bib]      [code]

Wasserstein barycenters can be computed in polynomial time in fixed dimension
Jason M Altschuler, Enric Boix-Adsera, 2021.
[abs][pdf][bib]      [code]

Banach Space Representer Theorems for Neural Networks and Ridge Splines
Rahul Parhi, Robert D. Nowak, 2021.
[abs][pdf][bib]

High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm
Wenlong Mou, Yi-An Ma, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan, 2021.
[abs][pdf][bib]

From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction
Henning Lange, Steven L. Brunton, J. Nathan Kutz, 2021.
[abs][pdf][bib]      [code]

Residual Energy-Based Models for Text
Anton Bakhtin, Yuntian Deng, Sam Gross, Myle Ott, Marc'Aurelio Ranzato, Arthur Szlam, 2021.
[abs][pdf][bib]

giotto-tda: : A Topological Data Analysis Toolkit for Machine Learning and Data Exploration
Guillaume Tauzin, Umberto Lupo, Lewis Tunstall, Julian Burella Pérez, Matteo Caorsi, Anibal M. Medina-Mardones, Alberto Dassatti, Kathryn Hess, 2021. (Machine Learning Open Source Software Paper)
[abs][pdf][bib]      [code]

Risk-Averse Learning by Temporal Difference Methods with Markov Risk Measures
Umit Köse, Andrzej Ruszczyński, 2021.
[abs][pdf][bib]

A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables
Zhao Tang Luo, Huiyan Sang, Bani Mallick, 2021.
[abs][pdf][bib]

Multi-class Gaussian Process Classification with Noisy Inputs
Carlos Villacampa-Calvo, Bryan Zaldívar, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, 2021.
[abs][pdf][bib]      [code]

Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation
Melkior Ornik, Ufuk Topcu, 2021.
[abs][pdf][bib]

Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection
Imtiaz Ahmed, Xia Ben Hu, Mithun P. Acharya, Yu Ding, 2021.
[abs][pdf][bib]      [code]

Asynchronous Online Testing of Multiple Hypotheses
Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan, 2021.
[abs][pdf][bib]

Learning interaction kernels in heterogeneous systems of agents from multiple trajectories
Fei Lu, Mauro Maggioni, Sui Tang, 2021.
[abs][pdf][bib]      [code]

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference
Tianyu Wang, Marco Morucci, M. Usaid Awan, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky, 2021.
[abs][pdf][bib]

A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
Oliver Kroemer, Scott Niekum, George Konidaris, 2021.
[abs][pdf][bib]

Single and Multiple Change-Point Detection with Differential Privacy
Wanrong Zhang, Sara Krehbiel, Rui Tuo, Yajun Mei, Rachel Cummings, 2021.
[abs][pdf][bib]

Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Julian Zimmert, Yevgeny Seldin, 2021.
[abs][pdf][bib]

Inference In High-dimensional Single-Index Models Under Symmetric Designs
Hamid Eftekhari, Moulinath Banerjee, Ya'acov Ritov, 2021.
[abs][pdf][bib]      [code]

Finite Time LTI System Identification
Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh, 2021.
[abs][pdf][bib]

Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions
Yunwen Lei, Ting Hu, Ke Tang, 2021.
[abs][pdf][bib]

Entangled Kernels - Beyond Separability
Riikka Huusari, Hachem Kadri, 2021.
[abs][pdf][bib]      [code]

A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems
Giulio Galvan, Matteo Lapucci, Chih-Jen Lin, Marco Sciandrone, 2021.
[abs][pdf][bib]

When random initializations help: a study of variational inference for community detection
Purnamrita Sarkar, Y. X. Rachel Wang, Soumendu S. Mukherjee, 2021.
[abs][pdf][bib]

A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters
Lei Yang, Jia Li, Defeng Sun, Kim-Chuan Toh, 2021.
[abs][pdf][bib]

Aggregated Hold-Out
Guillaume Maillard, Sylvain Arlot, Matthieu Lerasle, 2021.
[abs][pdf][bib]

Ranking and synchronization from pairwise measurements via SVD
Alexandre d'Aspremont, Mihai Cucuringu, Hemant Tyagi, 2021.
[abs][pdf][bib]

A Unified Sample Selection Framework for Output Noise Filtering: An Error-Bound Perspective
Gaoxia Jiang, Wenjian Wang, Yuhua Qian, Jiye Liang, 2021.
[abs][pdf][bib]

Continuous Time Analysis of Momentum Methods
Nikola B. Kovachki, Andrew M. Stuart, 2021.
[abs][pdf][bib]

Pykg2vec: A Python Library for Knowledge Graph Embedding
Shih-Yuan Yu, Sujit Rokka Chhetri, Arquimedes Canedo, Palash Goyal, Mohammad Abdullah Al Faruque, 2021. (Machine Learning Open Source Software Paper)
[abs][pdf][bib]      [code]

Simple and Fast Algorithms for Interactive Machine Learning with Random Counter-examples
Jagdeep Singh Bhatia, 2021.
[abs][pdf][bib]

On Multi-Armed Bandit Designs for Dose-Finding Trials
Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere, 2021.
[abs][pdf][bib]

Homogeneity Structure Learning in Large-scale Panel Data with Heavy-tailed Errors
Xiao Di, Yuan Ke, Runze Li, 2021.
[abs][pdf][bib]

Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit
Shenglong Zhou, Naihua Xiu, Hou-Duo Qi, 2021.
[abs][pdf][bib]

Unfolding-Model-Based Visualization: Theory, Method and Applications
Yunxiao Chen, Zhiliang Ying, Haoran Zhang, 2021.
[abs][pdf][bib]      [code]

Mixing Time of Metropolis-Hastings for Bayesian Community Detection
Bumeng Zhuo, Chao Gao, 2021.
[abs][pdf][bib]

Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm
Defeng Sun, Kim-Chuan Toh, Yancheng Yuan, 2021.
[abs][pdf][bib]

A Unified Framework for Random Forest Prediction Error Estimation
Benjamin Lu, Johanna Hardin, 2021.
[abs][pdf][bib]

Preference-based Online Learning with Dueling Bandits: A Survey
Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier, 2021.
[abs][pdf][bib]

Consistent estimation of small masses in feature sampling
Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro, 2021.
[abs][pdf][bib]

The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models
Carlos A. Gomez-Uribe, Brian Karrer, 2021.
[abs][pdf][bib]

An Empirical Study of Bayesian Optimization: Acquisition Versus Partition
Erich Merrill, Alan Fern, Xiaoli Fern, Nima Dolatnia, 2021.
[abs][pdf][bib]      [code]

Regulating Greed Over Time in Multi-Armed Bandits
Stefano Tracà, Cynthia Rudin, Weiyu Yan, 2021.
[abs][pdf][bib]      [code]

Domain Generalization by Marginal Transfer Learning
Gilles Blanchard, Aniket Anand Deshmukh, Urun Dogan, Gyemin Lee, Clayton Scott, 2021.
[abs][pdf][bib]      [code]

On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests
Krishnakumar Balasubramanian, Tong Li, Ming Yuan, 2021.
[abs][pdf][bib]

Full list

© JMLR 2021.