TMLR

A Survey on Out-of-Distribution Detection in NLP

Hao Lang, Yinhe Zheng, Yixuan Li, Jian Sun, Fei Huang, Yongbin Li

Comments TMLR

Identification of Negative Transfers in Multitask Learning Using Surrogate Models

Dongyue Li, Huy L. Nguyen, Hongyang R. Zhang

Comments 30 pages. Appeared in TMLR'23

SHAP-XRT: The Shapley Value Meets Conditional Independence Testing

Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam

Journal ref Transactions on Machine Learning Research (2023)

UnIVAL: Unified Model for Image, Video, Audio and Language Tasks

Mustafa Shukor, Corentin Dancette, Alexandre Rame, Matthieu Cord

Comments Accepted at TMLR 2023. 40 pages. Project page: https://unival-model.github.io/

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauza, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Żołna, Scott Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Tom Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

Comments Transactions on Machine Learning Research (12/2023)

Neural Implicit Manifold Learning for Topology-Aware Density Estimation

Brendan Leigh Ross, Gabriel Loaiza-Ganem, Anthony L. Caterini, Jesse C. Cresswell

Comments Accepted to TMLR in 2023. Code: https://github.com/layer6ai-labs/implicit-manifolds

IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

Jay Gala, Pranjal A. Chitale, Raghavan AK, Varun Gumma, Sumanth Doddapaneni, Aswanth Kumar, Janki Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, Pratyush Kumar, Mitesh M. Khapra, Raj Dabre, Anoop Kunchukuttan

Comments Accepted at TMLR

In Search of Projectively Equivariant Networks

Georg Bökman, Axel Flinth, Fredrik Kahl

Comments v3: Another significant rewrite. Accepted for publication in TMLR. v2: Significant rewrite. The title has been changed: "neural network" -> "network". More general description of projectively equivariant linear layers, with new proposed architectures, and a completely new accompanying experiment section, as a result

On the Efficacy of Differentially Private Few-shot Image Classification

Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Beguelin, Richard E Turner, Antti Honkela

Comments 49 pages, 24 figures; published in TMLR 12/2023 https://openreview.net/forum?id=hFsr59Imzm

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

POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning

Frederik Schubert, Carolin Benjamins, Sebastian Döhler, Bodo Rosenhahn, Marius Lindauer

Journal ref Transactions on Machine Learning Research, 2023

AmbientFlow: Invertible generative models from incomplete, noisy measurements

Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio

Comments Accepted to Transactions on Machine Learning Research (TMLR). OpenReview: https://openreview.net/forum?id=txpYITR8oa

Accelerating Batch Active Learning Using Continual Learning Techniques

Arnav Das, Gantavya Bhatt, Megh Bhalerao, Vianne Gao, Rui Yang, Jeff Bilmes

Comments Appeared in TMLR 2023

Early Stopping for Deep Image Prior

Hengkang Wang, Taihui Li, Zhong Zhuang, Tiancong Chen, Hengyue Liang, Ju Sun

Comments Published in TMLR (https://openreview.net/forum?id=231ZzrLC8X)

Journal ref Transactions on Machine Learning Research (TMLR), 2835-8856 (12/2023)

Local Function Complexity for Active Learning via Mixture of Gaussian Processes

Danny Panknin, Stefan Chmiela, Klaus-Robert Müller, Shinichi Nakajima

Comments 30 pages (+18 pages of references and appendices), 20 figures

Journal ref Transactions on Machine Learning Research, December 2023

Towards Stability of Autoregressive Neural Operators

Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown

Journal ref Transactions on Machine Learning Research. November 2023

Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants

Dennis J. N. J. Soemers, Vegard Mella, Eric Piette, Matthew Stephenson, Cameron Browne, Olivier Teytaud

Journal ref This preprint is superceded by the 2023 TMLR publication: https://openreview.net/forum?id=vJcTm2v9Ku

GIT-Net: Generalized Integral Transform for Operator Learning

Chao Wang, Alexandre Hoang Thiery

Journal ref Transactions on Machine Learning Research (05 Dec 2023)

Revisiting Topic-Guided Language Models

Carolina Zheng, Keyon Vafa, David M. Blei

Comments Published in Transactions on Machine Learning Research (TMLR) (12/2023)

Revisiting Hidden Representations in Transfer Learning for Medical Imaging

Dovile Juodelyte, Amelia Jiménez-Sánchez, Veronika Cheplygina

Comments Published in TMLR

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang

Comments 29 pages, 12 figures, Published in Transactions on Machine Learning Research (TMLR)

Relating graph auto-encoders to linear models

Solveig Klepper, Ulrike von Luxburg

Comments accepted to TMLR

Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods

Avery Ma, Yangchen Pan, Amir-massoud Farahmand

Comments Accepted at TMLR (Featured Certification). Code: see https://github.com/averyma/opt-robust

Improved identification accuracy in equation learning via comprehensive $\boldsymbol{R^2}$-elimination and Bayesian model selection

Daniel Nickelsen, Bubacarr Bah

Comments 12 pages main text and 11 pages appendix, Published in TMLR (https://openreview.net/forum?id=0ck7hJ8EVC)

Journal ref Transactions on Machine Learning Research (TMLR), 2835-8856 (11/2023)

HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms

Uddeshya Upadhyay, Sairam Bade, Arjun Puranik, Shahir Asfahan, Melwin Babu, Francisco Lopez-Jimenez, Samuel J. Asirvatham, Ashim Prasad, Ajit Rajasekharan, Samir Awasthi, Rakesh Barve

Comments Published at TMLR

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

Variational Elliptical Processes

Maria Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schöon

Comments 14 pages, 15 figures, appendix 9 pages

Journal ref Transactions on Machine Learning Research, September 2023

Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies

Shivakanth Sujit, Pedro H. M. Braga, Jorg Bornschein, Samira Ebrahimi Kahou

Comments TMLR 2023

Addressing caveats of neural persistence with deep graph persistence

Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke

Comments Transactions on Machine Learning Research (TMLR), 2023

Learn the Time to Learn: Replay Scheduling in Continual Learning

Marcus Klasson, Hedvig Kjellström, Cheng Zhang

Comments Published in TMLR (2023)

Replay-enhanced Continual Reinforcement Learning

Tiantian Zhang, Kevin Zehua Shen, Zichuan Lin, Bo Yuan, Xueqian Wang, Xiu Li, Deheng Ye

Comments Accepted by Transactions on Machine Learning Research 2023

Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph

Haonan Wang, Jieyu Zhang, Qi Zhu, Wei Huang, Kenji Kawaguchi, Xiaokui Xiao

Comments This article has been accepted for publication by the Transactions on Machine Learning Research. OpenReview at: https://openreview.net/forum?id=244KePn09i