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