ICML

Cold Posteriors and Aleatoric Uncertainty

Ben Adlam, Jasper Snoek, Samuel L. Smith

Comments 5 pages, 3 figures

Journal ref ICML workshop on Uncertainty and Robustness in Deep Learning (2020)

Scalable Derivative-Free Optimization for Nonlinear Least-Squares Problems

Coralia Cartis, Tyler Ferguson, Lindon Roberts

Comments Fixed author spelling

Journal ref Workshop on "Beyond first-order methods in ML systems" at the 37th International Conference on Machine Learning, 2020

Training Neural Networks for and by Interpolation

Leonard Berrada, Andrew Zisserman, M. Pawan Kumar

Comments Published at ICML 2020

Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient

Yufei Wang, Tianwei Ni

Comments published at 7th ICML Workshop on Automated Machine Learning (2020)

IIT Kanpur Consulting Group: Using Machine Learning and Management Consulting for Social Good

Tushar Goswamy, Vatsalya Tandon, Naishadh Parmar, Raunak Shah, Ayush Gupta

Comments 4 pages. Accepted to the ICML 2020 Workshop on Healthcare Systems, Population Health, and the Role of Health-Tech

Structural Language Models of Code

Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav

Comments Appeared in ICML'2020

Solving Partial Assignment Problems using Random Clique Complexes

Charu Sharma, Deepak Nathani, Manohar Kaul

Comments Accepted as a long talk at ICML 2018

Rademacher Complexity for Adversarially Robust Generalization

Dong Yin, Kannan Ramchandran, Peter Bartlett

Comments ICML 2019

Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning

Dong Yin, Yudong Chen, Kannan Ramchandran, Peter Bartlett

Comments ICML 2019

Adversarial Robustness Against the Union of Multiple Perturbation Models

Pratyush Maini, Eric Wong, J. Zico Kolter

Comments ICML 2020 Final Version

A Hybrid Approach to Audio-to-Score Alignment

Ruchit Agrawal, Simon Dixon

Comments ML4MD at ICML 2019

Structured Weight Priors for Convolutional Neural Networks

Tim Pearce, Andrew Y. K. Foong, Alexandra Brintrup

Comments Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu

Comments ICML 2020. Project page: https://liqing-ustc.github.io/NGS

Multi-Object Representation Learning with Iterative Variational Inference

Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, Alexander Lerchner

Journal ref ICML 2019 (PMLR 97:2424-2433)

Autoregressive flow-based causal discovery and inference

Ricardo Pio Monti, Ilyes Khemakhem, Aapo Hyvarinen

Comments 6 pages, 3 figures. Accepted at the 2nd ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models

On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models

Amine Echraibi, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton

Journal ref ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, Jul 2020, Vienna, Austria

History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms

Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang

Comments 46 pages, 23 figures; Published in ICML 2020

Feature Selection using Stochastic Gates

Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger

Comments Published in ICML 2020

Journal ref Proceedings of Machine Learning and Systems 2020, pages 8952--8963

Graph Optimal Transport for Cross-Domain Alignment

Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu

Journal ref ICML 2020

Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space

Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang

Comments to appear in ICML 2020

Creating Synthetic Datasets via Evolution for Neural Program Synthesis

Alexander Suh, Yuval Timen

Comments 10 pages, 0 figures, submitted to ICML 2020; experiments on Karel domain added

Estimating the number and effect sizes of non-null hypotheses

Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson

Comments ICML 2020

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy

Comments Presented at ICML 2020

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies

Shengpu Tang, Aditya Modi, Michael W. Sjoding, Jenna Wiens

Comments ICML 2020. Code available at https://github.com/shengpu1126/RL-Set-Valued-Policy

Monte-Carlo Tree Search as Regularized Policy Optimization

Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Rémi Munos

Comments Accepted to International Conference on Machine Learning (ICML), 2020

Interpreting Spatially Infinite Generative Models

Chaochao Lu, Richard E. Turner, Yingzhen Li, Nate Kushman

Comments ICML 2020 workshop on Human Interpretability in Machine Learning (WHI 2020)

Serverless inferencing on Kubernetes

Clive Cox, Dan Sun, Ellis Tarn, Animesh Singh, Rakesh Kelkar, David Goodwin

Comments 4 pages, 1 figure, presented at workshop on "Challenges in Deploying and Monitoring Machine Learning System" at ICML 2020

Finding trainable sparse networks through Neural Tangent Transfer

Tianlin Liu, Friedemann Zenke

Comments Accepted by ICML 2020

GMNN: Graph Markov Neural Networks

Meng Qu, Yoshua Bengio, Jian Tang

Comments icml 2019

Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP

Satyen Kale, Zohar Karnin, Tengyuan Liang, Dávid Pál

Comments Appearing in 34th International Conference on Machine Learning (ICML), 2017

Journal ref Proceedings of the 34th International Conference on Machine Learning 70 (2017) 1780-1788