ICML

Simple Regularisation for Uncertainty-Aware Knowledge Distillation

Martin Ferianc, Miguel Rodrigues

Comments Accepted to the ICML 2022 Workshop on Distribution-Free Uncertainty Quantification. The code can be found at: https://github.com/martinferianc/hydra_plus

Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems

Lukas Köhs, Bastian Alt, Heinz Koeppl

Comments Accepted at ICML 2022

Describing Differences between Text Distributions with Natural Language

Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

Comments International Conference on Machine Learning, 2022

Translatotron 2: High-quality direct speech-to-speech translation with voice preservation

Ye Jia, Michelle Tadmor Ramanovich, Tal Remez, Roi Pomerantz

Comments ICML 2022

SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals

Dani Kiyasseh, Tingting Zhu, David A. Clifton

Comments ICML 2022

On the Efficiency of Entropic Regularized Algorithms for Optimal Transport

Tianyi Lin, Nhat Ho, Michael I. Jordan

Comments Accepted by Journal of Machine Learning Research; A preliminary version [arXiv:1901.06482] of this paper, with a subset of the results that are presented here, was presented at ICML 2019; 39 pages, 21 figures

DNNR: Differential Nearest Neighbors Regression

Youssef Nader, Leon Sixt, Tim Landgraf

Comments published at ICML 2022

DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning

Hassam Sheikh, Kizza Frisbee, Mariano Phielipp

Comments Accepted for Publication at ICML 2022

$\mathscr{H}$-Consistency Estimation Error of Surrogate Loss Minimizers

Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Comments ICML 2022 (long presentation)

Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning

Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair, Patrick Yin, Sergey Levine

Comments ICML 2022. 20 Pages, 15 Figures, 4 Tables. Website at https://sites.google.com/view/gc-bisimulation

The Primacy Bias in Deep Reinforcement Learning

Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron Courville

Comments ICML 2022; code at https://github.com/evgenii-nikishin/rl_with_resets

Diffusion Models for Adversarial Purification

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar

Comments ICML 2022

Policy Gradient Method For Robust Reinforcement Learning

Yue Wang, Shaofeng Zou

Comments Accepted by ICML 2022

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian

Comments To appear in ICML 2022

Best-Response Dynamics and Fictitious Play in Identical-Interest and Zero-Sum Stochastic Games

Lucas Baudin, Rida Laraki

Comments Preprint, accepted at ICML 2022

Scaling Out-of-Distribution Detection for Real-World Settings

Dan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joe Kwon, Mohammadreza Mostajabi, Jacob Steinhardt, Dawn Song

Comments ICML 2022; The Species dataset and code are available at https://github.com/hendrycks/anomaly-seg

Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memes

Sunil Gundapu, Radhika Mamidi

Comments Paper accepted at 2nd International Conference on Machine Learning Techniques and Data Science (MLDS 2021)

Differentially private training of residual networks with scale normalisation

Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, Georgios Kaissis

Comments Submitted as paper to TPDP at ICML 2022

Leveraging Language to Learn Program Abstractions and Search Heuristics

Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas

Comments appeared in Thirty-eighth International Conference on Machine Learning (ICML 2021)

A Probabilistic Interpretation of Transformers

Alexander Shim

Comments Accepted in ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception

I-BERT: Integer-only BERT Quantization

Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer

Journal ref ICML 2021 (Oral)

A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems

Timo Bertram, Johannes Fürnkranz, Martin Müller

Comments arXiv admin note: substantial text overlap with arXiv:2105.11864

Journal ref SubSetML: Subset Selection in Machine Learning: From Theory to Practice @ ICML 2021

Predicting Real-time Scientific Experiments Using Transformer models and Reinforcement Learning

Juan Manuel Parrilla-Gutierrez

Comments 8 pages, 5 figures, conference

Journal ref 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021, pp. 502-506

Computing the Collection of Good Models for Rule Lists

Kota Mata, Kentaro Kanamori, Hiroki Arimura

Comments 16 pages, 4 Figures, to applear in the 18th International Conference on Machine Learning and Data Mining (MLDM 2022 ), July 16 - 21, 2022, New York, USA

On the Convergence and Robustness of Adversarial Training

Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu

Comments ICML 2019 Long Talk. Fixing bugs in the proof of Theorem 1

Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces

Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, Yuan Yao

Comments This is the journal extension version of the ICML conference paper, "DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths"

Journal ref International Conference on Machine Learning. PMLR, 2020, pp. 3315--3326

Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability

Timo Bertram, Johannes Fürnkranz, Martin Müller

Comments Preliminary work under review for ICML 2022

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths

Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao

Comments conference , 23 pages https://github.com/corwinliu9669/dS2LBI. arXiv admin note: text overlap with arXiv:1905.09449

Journal ref ICML 2020

Character-focused Video Thumbnail Retrieval

Shervin Ardeshir, Nagendra Kamath, Hossein Taghavi

Comments International Conference on Machine Learning. Machine Learning for Media Discovery (ML4MD) Workshop 2020

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation

Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang

Comments Published in ICML 2021