TMLR

Dual Cognitive Architecture: Incorporating Biases and Multi-Memory Systems for Lifelong Learning

Shruthi Gowda, Bahram Zonooz, Elahe Arani

Comments Published in Transactions on Machine Learning Research (TMLR)

Private Multi-Task Learning: Formulation and Applications to Federated Learning

Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith

Comments Accepted to TMLR. Transactions on Machine Learning Research (2022)

Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning

Filippos Christianos, Georgios Papoudakis, Stefano V. Albrecht

Comments Published in Transactions on Machine Learning Research (TMLR); Reviewed on OpenReview: https://openreview.net/forum?id=3AzqYa18ah

Asymptotic Analysis of Conditioned Stochastic Gradient Descent

Rémi Leluc, François Portier

Comments Accepted to Transactions on Machine Learning Research 2023

Journal ref Transactions on Machine Learning Research (2023)

Identifying latent distances with Finslerian geometry

Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg

Comments 36 pages, 12 figures, accepted at TMLR (October 2023)

Dynamic Subgoal-based Exploration via Bayesian Optimization

Yijia Wang, Matthias Poloczek, Daniel R. Jiang

Journal ref Transactions on Machine Learning Research (09/2023)

Federated Learning of Large Models at the Edge via Principal Sub-Model Training

Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr

Comments 19 pages, 11 figures. Accepted to Transactions on Machine Learning Research (TMLR) 2023 Code: https://github.com/yuehniu/modeldecomp-fl

Learning domain-specific causal discovery from time series

Xinyue Wang, Konrad Paul Kording

Comments 16 main pages, 7 figures. Accepted by TMLR

Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations

Xinyu Yang, Huaxiu Yao, Allan Zhou, Chelsea Finn

Comments Accepted by TMLR

Private GANs, Revisited

Alex Bie, Gautam Kamath, Guojun Zhang

Comments 28 pages; revisions and new experiments from TMLR camera-ready + code release at https://github.com/alexbie98/dpgan-revisit

Learning Object-Centric Neural Scattering Functions for Free-Viewpoint Relighting and Scene Composition

Hong-Xing Yu, Michelle Guo, Alireza Fathi, Yen-Yu Chang, Eric Ryan Chan, Ruohan Gao, Thomas Funkhouser, Jiajun Wu

Comments Journal extension of arXiv:2012.08503 (TMLR 2023). The first two authors contributed equally to this work. Project page: https://kovenyu.com/osf/

Journal ref Transactions on Machine Learning Research (TMLR), 2023

Holistic Evaluation of Language Models

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

Comments Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Project page: https://crfm.stanford.edu/helm/v1.0

Journal ref Published in Transactions on Machine Learning Research (TMLR), 2023

An Optical Control Environment for Benchmarking Reinforcement Learning Algorithms

Abulikemu Abuduweili, Changliu Liu

Comments Transactions on Machine Learning Research (2023)

IBIA: An Incremental Build-Infer-Approximate Framework for Approximate Inference of Partition Function

Shivani Bathla, Vinita Vasudevan

Comments Pages: 24(main) 3(references) 4(appendix), Figures: 5, Tables: 7

Journal ref Transaction on Machine Learning Research (TMLR), 09/2023

Label Noise-Robust Learning using a Confidence-Based Sieving Strategy

Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis

Comments https://openreview.net/forum?id=3taIQG4C7H

Journal ref Transactions on Machine Learning Research, 2835-8856, 2023

Data Distillation: A Survey

Noveen Sachdeva, Julian McAuley

Comments Accepted at TMLR '23. 21 pages, 4 figures

Projected Randomized Smoothing for Certified Adversarial Robustness

Samuel Pfrommer, Brendon G. Anderson, Somayeh Sojoudi

Comments Transactions on Machine Learning Research (TMLR) 2023

Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data

Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada

Comments Transactions on Machine Learning Research 2023

A Survey on Transformers in Reinforcement Learning

Wenzhe Li, Hao Luo, Zichuan Lin, Chongjie Zhang, Zongqing Lu, Deheng Ye

Comments Accepted by TMLR

Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning

Andreas Kirsch, Sebastian Farquhar, Parmida Atighehchian, Andrew Jesson, Frederic Branchaud-Charron, Yarin Gal

Comments TMLR Paper: https://openreview.net/forum?id=vcHwQyNBjW

RIFLE: Imputation and Robust Inference from Low Order Marginals

Sina Baharlouei, Kelechi Ogudu, Sze-chuan Suen, Meisam Razaviyayn

Comments 36 pages, 11 figures

Journal ref Transaction on Machine Learning Research (TMLR), 09/2023

Fairness and robustness in anti-causal prediction

Maggie Makar, Alexander D'Amour

Journal ref Published in TMLR, 2022

TSMixer: An All-MLP Architecture for Time Series Forecasting

Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan O. Arik, Tomas Pfister

Journal ref Transactions on Machine Learning Research (TMLR), 09/2023

Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression

Alexander Norcliffe, Lev Proleev, Diana Mincu, Fletcher Lee Hartsell, Katherine Heller, Subhrajit Roy

Comments 32 pages, 2 figures, 17 tables, published in TMLR 2023

Understanding convolution on graphs via energies

Francesco Di Giovanni, James Rowbottom, Benjamin P. Chamberlain, Thomas Markovich, Michael M. Bronstein

Comments Accepted at TMLR; First two authors equal contribution; 35 pages

V1T: large-scale mouse V1 response prediction using a Vision Transformer

Bryan M. Li, Isabel M. Cornacchia, Nathalie L. Rochefort, Arno Onken

Comments updated references and added link to code repository; add analysis on generalization and visualize aRFs; updated with TMLR publication

Semantic Representations of Mathematical Expressions in a Continuous Vector Space

Neeraj Gangwar, Nickvash Kani

Comments Transactions on Machine Learning Research (TMLR), September 2023

RECLIP: Resource-efficient CLIP by Training with Small Images

Runze Li, Dahun Kim, Bir Bhanu, Weicheng Kuo

Comments Published at Transactions on Machine Learning Research

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings

Comments Paper accompanying Open-Source Software from https://github.com/IntelLabs/matsciml

Journal ref Transactions on Machine Learning Research (2023)

Cyclophobic Reinforcement Learning

Stefan Sylvius Wagner, Peter Arndt, Jan Robine, Stefan Harmeling

Comments Published in Transactions on Machine Learning Research (08/2023)