TMLR

From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality

Fusheng Liu, Haizhao Yang, Soufiane Hayou, Qianxiao Li

Journal ref Transactions on Machine Learning Research 2022

Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent

Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain

Comments Accepted to TMLR

FedShuffle: Recipes for Better Use of Local Work in Federated Learning

Samuel Horváth, Maziar Sanjabi, Lin Xiao, Peter Richtárik, Michael Rabbat

Comments Published in Transactions on Machine Learning Research (09/2022)

GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation

Haibo Qiu, Baosheng Yu, Dacheng Tao

Comments Published in Transactions on Machine Learning Research (09/2022)

MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks

Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski

Comments To appear at the Transactions on Machine Learning Research (TMLR)

LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling

Jinsung Yoon, Sercan O. Arik, Tomas Pfister

Comments Published in Transactions on Machine Learning Research (TMLR) - September, 2022 - https://openreview.net/forum?id=S8eABAy8P3

Estimating Potential Outcome Distributions with Collaborating Causal Networks

Tianhui Zhou, William E Carson, David Carlson

Comments https://openreview.net/forum?id=q1Fey9feu7

Journal ref Transactions on Machine Learning Research, 2022

Weight Expansion: A New Perspective on Dropout and Generalization

Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang

Comments TMLR

DR-DSGD: A Distributionally Robust Decentralized Learning Algorithm over Graphs

Chaouki Ben Issaid, Anis Elgabli, Mehdi Bennis

Comments Accepted at Transactions on Machine Learning Research (TMLR)

Recurrent networks, hidden states and beliefs in partially observable environments

Gaspard Lambrechts, Adrien Bolland, Damien Ernst

Comments 12 pages, 28 pages total, 20 figures. Transactions on Machine Learning Research (2022)

Journal ref Transactions on Machine Learning Research, 2022

Centroids Matching: an efficient Continual Learning approach operating in the embedding space

Jary Pomponi, Simone Scardapane, Aurelio Uncini

Comments Submitted to Transactions on Machine Learning Research (TMLR)

On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning

Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri

Journal ref Transactions on Machine Learning Research, 2022

HEAT: Hyperedge Attention Networks

Dobrik Georgiev, Marc Brockschmidt, Miltiadis Allamanis

Comments Published in TMLR

SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning

Marco Bagatella, Sammy Christen, Otmar Hilliges

Comments Accepted by TMLR in August 2022. Project page at https://eth-ait.github.io/sfp/

Efficient CDF Approximations for Normalizing Flows

Chandramouli Shama Sastry, Andreas Lehrmann, Marcus Brubaker, Alexander Radovic

Comments Accepted to TMLR

Equivariant Mesh Attention Networks

Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen

Comments Published in Transactions on Machine Learning Research (08/2022). Official code made available at https://github.com/gallego-posada/eman - For the OpenReview entry, see https://openreview.net/forum?id=3IqqJh2Ycy

Zero-Shot Learning with Common Sense Knowledge Graphs

Nihal V. Nayak, Stephen H. Bach

Comments Paper published in TMLR

Optimal Client Sampling for Federated Learning

Wenlin Chen, Samuel Horvath, Peter Richtarik

Comments Published in Transactions on Machine Learning Research, code available: https://github.com/SamuelHorvath/FL-optimal-client-sampling

Attentive Walk-Aggregating Graph Neural Networks

Mehmet F. Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang

Comments Published in TMLR (Transactions on Machine Learning Research) (08/2022) 32 pages

High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Florian Bordes, Randall Balestriero, Pascal Vincent

Comments Accepted at TMLR 2022

Meta-Learning Sparse Compression Networks

Jonathan Richard Schwarz, Yee Whye Teh

Comments Published in TMLR (2022)

Deep Classifiers with Label Noise Modeling and Distance Awareness

Vincent Fortuin, Mark Collier, Florian Wenzel, James Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Comments Published in TMLR

Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O. Arik, Chen-Yu Lee, Tomas Pfister

Comments Published in Transactions on Machine Learning Research (TMLR) - August, 2022 - https://openreview.net/forum?id=b3v1UrtF6G

NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels

Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama

Comments Accepted at Transactions on Machine Learning Research (TMLR) at June 2022

Journal ref Transactions on Machine Learning Research, 2022

Stable and Interpretable Unrolled Dictionary Learning

Bahareh Tolooshams, Demba Ba

Comments Published in Transactions on Machine Learning Research (TMLR) (08/2022)

Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization

David Peer, Bart Keulen, Sebastian Stabinger, Justus Piater, Antonio Rodríguez-Sánchez

Comments Accepted at TMLR (07/2022): https://openreview.net/forum?id=LJohl5DnZf

On Learning the Transformer Kernel

Sankalan Pal Chowdhury, Adamos Solomou, Avinava Dubey, Mrinmaya Sachan

Comments Accepted to TMLR

How Expressive are Transformers in Spectral Domain for Graphs?

Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Hiroki Kanezashi, Toyotaro Suzumura, Isaiah Onando Mulang'

Comments Accepted in Transactions on Machine Learning Research

The Graph Cut Kernel for Ranked Data

Michelangelo Conserva, Marc Peter Deisenroth, K S Sesh Kumar

Journal ref Transactions on Machine Learning Research (2022)

Identifying Causal Structure in Dynamical Systems

Dominik Baumann, Friedrich Solowjow, Karl H. Johansson, Sebastian Trimpe

Comments Accepted final versions to appear in the Transactions on Machine Learning Research