TMLR

Single Image Test-Time Adaptation for Segmentation

Klara Janouskova, Tamir Shor, Chaim Baskin, Jiri Matas

Comments TMLR accepted paper

Semi-Supervised Semantic Segmentation via Marginal Contextual Information

Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii, Or Litany, Chaim Baskin

Comments Published at TMLR

Selective Pre-training for Private Fine-tuning

Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang

Comments Transactions on Machine Learning Research. Code available at https://github.com/dayu11/selective_pretraining_for_private_finetuning

Koopman Spectrum Nonlinear Regulators and Efficient Online Learning

Motoya Ohnishi, Isao Ishikawa, Kendall Lowrey, Masahiro Ikeda, Sham Kakade, Yoshinobu Kawahara

Comments 41 pages, 21 figures

Journal ref Transactions on Machine Learning Research (https://openreview.net/forum?id=thfoUZugvS), 2024

Fine-tuning can cripple your foundation model; preserving features may be the solution

Jishnu Mukhoti, Yarin Gal, Philip H. S. Torr, Puneet K. Dokania

Comments Published in TMLR: https://openreview.net/forum?id=kfhoeZCeW7

Bytes Are All You Need: Transformers Operating Directly On File Bytes

Maxwell Horton, Sachin Mehta, Ali Farhadi, Mohammad Rastegari

Journal ref Transactions on Machine Learning Research 2835-8856 (2024)

Multiple Kronecker RLS fusion-based link propagation for drug-side effect prediction

Yuqing Qian, Ziyu Zheng, Prayag Tiwari, Yijie Ding, Quan Zou

Comments Transactions on Machine Learning Research (TMLR 2024)

Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks

Ryuji Saiin, Tomoya Shirakawa, Sota Yoshihara, Yoshihide Sawada, Hiroyuki Kusumoto

Comments 14 pages, 5 figures, Appendix:10 pages, 2 figures, v6:Published in Transactions on Machine Learning Research

PNeRV: A Polynomial Neural Representation for Videos

Sonam Gupta, Snehal Singh Tomar, Grigorios G Chrysos, Sukhendu Das, A. N. Rajagopalan

Comments 25 pages, 17 figures, published at TMLR, Feb 2024

Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families

Vaidotas Simkus, Michael U. Gutmann

Comments Published in Transactions on Machine Learning Research (TMLR), 2024

Revisiting Active Learning in the Era of Vision Foundation Models

Sanket Rajan Gupte, Josiah Aklilu, Jeffrey J. Nirschl, Serena Yeung-Levy

Comments Accepted to TMLR

On the numerical reliability of nonsmooth autodiff: a MaxPool case study

Ryan Boustany

Journal ref Transactions on Machine Learning Research Journal, 2024, 23 p

Towards Unbiased Calibration using Meta-Regularization

Cheng Wang, Jacek Golebiowski

Comments 20 pages. Accepted at TMLR: https://openreview.net/forum?id=Yf8iHCfG4W

Hyperbolic Random Forests

Lars Doorenbos, Pablo Márquez-Neila, Raphael Sznitman, Pascal Mettes

Comments Accepted at TMLR. Code available at https://github.com/LarsDoorenbos/HoroRF

DeepReShape: Redesigning Neural Networks for Efficient Private Inference

Nandan Kumar Jha, Brandon Reagen

Comments Accepted to Transactions on Machine Learning Research (TMLR), 2024

Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting

Timm Hess, Eli Verwimp, Gido M. van de Ven, Tinne Tuytelaars

Comments TMLR 2024

Journal ref Transactions on Machine Learning Research (TMLR), 2024

Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection

Eduardo Dadalto, Florence Alberge, Pierre Duhamel, Pablo Piantanida

Comments Accepted for publication in Transactions on Machine Learning Research (TMLR)

Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey

Xi Fang, Weijie Xu, Fiona Anting Tan, Jiani Zhang, Ziqing Hu, Yanjun Qi, Scott Nickleach, Diego Socolinsky, Srinivasan Sengamedu, Christos Faloutsos

Comments 41 pages, 4 figures, 8 tables

Journal ref TMLR 2024

Chain-of-Thought Unfaithfulness as Disguised Accuracy

Oliver Bentham, Nathan Stringham, Ana Marasović

Comments TMLR accepted paper camera-ready version. First two authors contributed equally. 8 pages main, 13 pages appendix

TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality

Yinsong Wang, Shahin Shahrampour

Comments Accepted to TMLR

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Dongruo Zhou, Jinghui Chen, Yuan Cao, Ziyan Yang, Quanquan Gu

Comments 25 pages, 2 tables. Published in Transactions on Machine Learning Research (TMLR)

Revisiting Non-separable Binary Classification and its Applications in Anomaly Detection

Matthew Lau, Ismaila Seck, Athanasios P Meliopoulos, Wenke Lee, Eugene Ndiaye

Comments Accepted in Transactions on Machine Learning Research (TMLR) 2024. Code: https://github.com/mattlaued/XOR-is-Linearly-Classifiable

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation

Qi Yan, Zhengyang Liang, Yang Song, Renjie Liao, Lele Wang

Comments TMLR 2024

Bayesian Quantification with Black-Box Estimators

Albert Ziegler, Paweł Czyż

Comments A follow-up of arXiv:1908.09157

Journal ref Transactions on Machine Learning Research (2024). ISSN: 2835-8856. URL: https://openreview.net/forum?id=Ft4kHrOawZ

Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration

Kotaro Yoshida, Hiroki Naganuma

Comments Accepted to TMLR

Promoting Exploration in Memory-Augmented Adam using Critical Momenta

Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar

Comments Published in Transactions on Machine Learning Research

State-wise Constrained Policy Optimization

Weiye Zhao, Rui Chen, Yifan Sun, Tianhao Wei, Changliu Liu

Comments Published in Transactions of Machine Learning Research

Journal ref Transactions on Machine Learning Research (2024). ISSN: 2835-8856. https://openreview.net/forum?id=NgK5etmhz9

Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma

Comments Accepted to Transactions on Machine Learning Research (TMLR)

Optical Transformers

Maxwell G. Anderson, Shi-Yuan Ma, Tianyu Wang, Logan G. Wright, Peter L. McMahon

Comments 27 pages, 13 figures

Journal ref Transactions on Machine Learning Research, 03/2024, https://openreview.net/forum?id=Xxw0edFFQC

What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?

Weijie Tu, Weijian Deng, Liang Zheng, Tom Gedeon

Comments TMLR 2024 (https://openreview.net/forum?id=vtiDUgGjyx)