JMLR

Cluster-Specific Predictions with Multi-Task Gaussian Processes

Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey

Comments 47 pages

Journal ref Journal of Machine Learning Research (2023)

Intrinsic persistent homology via density-based metric learning

Ximena Fernández, Eugenio Borghini, Gabriel Mindlin, Pablo Groisman

Comments 37 pages. v3: major revision. Final version accepted for publication at Journal of Machine Learning Research

Gap Minimization for Knowledge Sharing and Transfer

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

Comments Journal of Machine Learning Research (JMLR) accepted

Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks

El Mehdi Achour, François Malgouyres, Franck Mamalet

Journal ref Journal of Machine Learning Research, 2022, 23 (347), pp.1--56

Uncertainty Estimation based on Geometric Separation

Gabriella Chouraqui, Liron Cohen, Gil Einziger, Liel Leman

Comments Submitted to JMLR. arXiv admin note: substantial text overlap with arXiv:2206.11562

Sampling random graph homomorphisms and applications to network data analysis

Hanbaek Lyu, Facundo Memoli, David Sivakoff

Comments 66 pages, 36 figures, 4 tables

Journal ref Journal of Machine Learning Research (2023)

Reinforcement Learning for Joint Optimization of Multiple Rewards

Mridul Agarwal, Vaneet Aggarwal

Comments Accepted JMLR, Jul 2022

Journal ref JMLR, 2022

Expanding boundaries of Gap Safe screening

Cassio F. Dantas, Emmanuel Soubies, Cédric Févotte

Journal ref Journal of Machine Learning Research, 2021, 22 (236), pp.1-57

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

Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer

Comments 44 pages, under review

Journal ref Journal of Machine Learning Research 23 (2022) 1-45

Task Weighting in Meta-learning with Trajectory Optimisation

Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro

Comments Revision after a peer review from JMLR

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

Comments 44 pages. arXiv admin note: text overlap with arXiv:2107.04479

Journal ref Journal of Machine Learning Research 23, 260 (2022), pp. 1-50

Benchmarking Graph Neural Networks

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

Comments Benchmarking framework on GitHub at https://github.com/graphdeeplearning/benchmarking-gnns

Journal ref Journal of Machine Learning Research (JMLR), 2022

Reward Shaping for Human Learning via Inverse Reinforcement Learning

Mark A. Rucker, Layne T. Watson, Matthew S. Gerber, Laura E. Barnes

Comments This paper has been modified considerably for resubmission to Journal of Machine Learning Research, for source code, see https://github.com/mrucker/kpirl-kla

Formal Privacy for Partially Private Data

Jeremy Seeman, Matthew Reimherr, Aleksandra Slavkovic

Comments 34 pages, 4 figures; submitted to JMLR

More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming

Vo Nguyen Le Duy, Ichiro Takeuchi

Journal ref Journal of Machine Learning Research 23.300 (2022): 1-37

d3rlpy: An Offline Deep Reinforcement Learning Library

Takuma Seno, Michita Imai

Comments Journal of Machine Learning Research

Journal ref Journal of Machine Learning Research 23(315) (2022) 1-20;

Novel min-max reformulations of Linear Inverse Problems

Mohammed Rayyan Sheriff, Debasish Chatterjee

Journal ref Journal of Machine Learning Research, Vol. 23, Paper No. 28, pp. 1-46, 2022

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

Raj Agrawal, Tamara Broderick

Comments To appear in the Journal of Machine Learning Research

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

Comments Accepted by Journal of Machine Learning Research in 11/2022

Journal ref Journal of Machine Learning Research 23 (2022) 1-41

Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning

Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau

Comments Published in JMLR: https://jmlr.org/papers/v21/20-312.html

The Separation Capacity of Random Neural Networks

Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk

Comments The current version of the manuscript has been accepted to Journal of Machine Learning Research

Journal ref J. Mach. Learn. Res. 23:309 (2022) 1-47

Interval-censored Hawkes processes

Marian-Andrei Rizoiu, Alexander Soen, Shidi Li, Pio Calderon, Leanne Dong, Aditya Krishna Menon, Lexing Xie

Journal ref Journal of Machine Learning Research, 23(338):1-84, 2022. https://jmlr.org/papers/v23/21-0917.html

The Geometry of Uniqueness, Sparsity and Clustering in Penalized Estimation

Ulrike Schneider, Patrick Tardivel

Journal ref Journal of Machine Learning Research 23 (2022), 1-36

Network Regression with Graph Laplacians

Yidong Zhou, Hans-Georg Müller

Comments 41 pages, 13 figures

Journal ref Journal of Machine Learning Research 23 (2022) 1-41 http://jmlr.org/papers/v23/22-0681.html

Fundamental Limits and Tradeoffs in Invariant Representation Learning

Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar

Comments JMLR camera-ready version

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

Bernardo Fichera, Aude Billard

Comments Paper Accepted at Journal of Machine Learning Research 23 (2022)

Handling Hard Affine SDP Shape Constraints in RKHSs

Pierre-Cyril Aubin-Frankowski, Zoltan Szabo

Journal ref Journal of Machine Learning Research 23 (2022) 1-53

Metrics of calibration for probabilistic predictions

Imanol Arrieta-Ibarra, Paman Gujral, Jonathan Tannen, Mark Tygert, Cherie Xu

Comments 50 pages, 36 figures

Journal ref Journal of Machine Learning Research, 23: 1-54, 2022

IALE: Imitating Active Learner Ensembles

Christoffer Loeffler, Christopher Mutschler

Comments 17 pages

Journal ref Journal of Machine Learning Research 23 (2022) 1-29

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

T. Tony Cai, Rong Ma

Comments Accepted by Journal of Machine Learning Research