ICML

How Good is the Bayes Posterior in Deep Neural Networks Really?

Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Świątkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Comments Full version (main paper and appendix) of the ICML 2020 publication

Outlier Detection through Null Space Analysis of Neural Networks

Matthew Cook, Alina Zare, Paul Gader

Comments 6 pages, 4 figures, Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning

Scene Graph Reasoning for Visual Question Answering

Marcel Hildebrandt, Hang Li, Rajat Koner, Volker Tresp, Stephan Günnemann

Comments ICML Workshop Graph Representation Learning and Beyond (GRL+)

Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?

Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry

Comments ICML 2020

Structure Adaptive Algorithms for Stochastic Bandits

Rémy Degenne, Han Shao, Wouter M. Koolen

Comments 10+18 pages. To be published in the proceedings of ICML 2020

Gamification of Pure Exploration for Linear Bandits

Rémy Degenne, Pierre Ménard, Xuedong Shang, Michal Valko

Comments 11+25 pages. To be published in the proceedings of ICML 2020

A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton

Risheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang

Comments Accepted at ICML 2020

Neural Contextual Bandits with UCB-based Exploration

Dongruo Zhou, Lihong Li, Quanquan Gu

Comments 27 pages, 2 figures, 1 table. In ICML 2020

Adversarial Neural Pruning with Latent Vulnerability Suppression

Divyam Madaan, Jinwoo Shin, Sung Ju Hwang

Comments Accepted to ICML 2020. Code available at https://github.com/divyam3897/ANP_VS

Feature Extraction on Synthetic Black Hole Images

Joshua Yao-Yu Lin, George N. Wong, Ben S. Prather, Charles F. Gammie

Comments Accepted by ML Interpretability for Scientific Discovery Workshop at ICML 2020

Sequential Transfer in Reinforcement Learning with a Generative Model

Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli

Comments ICML 2020

Graph Homomorphism Convolution

Hoang NT, Takanori Maehara

Comments 37th International Conference on Machine Learning (ICML 2020)

Journal ref PMLR 119, 2020

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently

Asaf Cassel, Alon Cohen, Tomer Koren

Comments Accepted for presentation at International Conference on Machine Learning (ICML) 2020

Test-Time Training with Self-Supervision for Generalization under Distribution Shifts

Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt

Comments ICML 2020

All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

Comments ICML 2020

Towards Explainable Graph Representations in Digital Pathology

Guillaume Jaume, Pushpak Pati, Antonio Foncubierta-Rodriguez, Florinda Feroce, Giosue Scognamiglio, Anna Maria Anniciello, Jean-Philippe Thiran, Orcun Goksel, Maria Gabrani

Comments ICML'20 workshop on Computational Biology

A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition

Anurag Kumar, Vamsi Krishna Ithapu

Comments Accepted International Conference on Machine Learning $\textbf{(ICML) 2020}$. 14 pages

Adversarial Mutual Information for Text Generation

Boyuan Pan, Yazheng Yang, Kaizhao Liang, Bhavya Kailkhura, Zhongming Jin, Xian-Sheng Hua, Deng Cai, Bo Li

Comments Published at ICML 2020

Conditional Set Generation with Transformers

Adam R Kosiorek, Hyunjik Kim, Danilo J Rezende

Comments 6 pages, 6 figures, ICML 2020 Workshop on Object-Oriented Learning

DeltaGrad: Rapid retraining of machine learning models

Yinjun Wu, Edgar Dobriban, Susan B. Davidson

Journal ref published in ICML 2020

A benchmark study on reliable molecular supervised learning via Bayesian learning

Doyeong Hwang, Grace Lee, Hanseok Jo, Seyoul Yoon, Seongok Ryu

Comments To be appeared in ICML 2020 Workshop "Uncertainty and Robustness in Deep Learning"

Planning to Explore via Self-Supervised World Models

Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak

Comments Accepted at ICML 2020. Videos and code at https://ramanans1.github.io/plan2explore/

XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning

Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon

Comments In Proceedings of the 37th International Conference on Machine Learning (ICML) 2020, Vienna, Austria, PMLR 119; *Equal contribution

Journal ref Proceedings of the 37th International Conference on Machine Learning (ICML) 2020, Vienna, Austria, PMLR 119

Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks

Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein

Comments ICML 2020

A Simple Framework for Contrastive Learning of Visual Representations

Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton

Comments ICML'2020. Code and pretrained models at https://github.com/google-research/simclr

Sequential Cooperative Bayesian Inference

Junqi Wang, Pei Wang, Patrick Shafto

Comments 25 pages, 22 figures, accepted by ICML 2020

Normalizing Flows on Tori and Spheres

Danilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer

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

Learning De-biased Representations with Biased Representations

Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun, Jaegul Choo, Seong Joon Oh

Comments Accepted to ICML 2020. Code available at https://github.com/clovaai/rebias

Fiduciary Bandits

Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz

Comments Published in The Thirty-seventh International Conference on Machine Learning (ICML 2020)

Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization

Rie Johnson, Tong Zhang

Comments ICML 2020