ICML

Creation of User Friendly Datasets: Insights from a Case Study concerning Explanations of Loan Denials

Ajay Chander, Ramya Srinivasan

Comments presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA

Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise

Henry W. J. Reeve, Ata Kaban

Comments ICML 2019

Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer

René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Natalia Díaz-Rodríguez, David Filliat

Comments accepted to the Workshop on Multi-Task and Lifelong Reinforcement Learning, ICML 2019

Few-Shot Point Cloud Region Annotation with Human in the Loop

Siddhant Jain, Sowmya Munukutla, David Held

Comments presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA

Meta-Learning Neural Bloom Filters

Jack W Rae, Sergey Bartunov, Timothy P Lillicrap

Comments International Conference on Machine Learning 2019

A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization

Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng

Comments Appears in ICML 2019

Sensitivity of Deep Convolutional Networks to Gabor Noise

Kenneth T. Co, Luis Muñoz-González, Emil C. Lupu

Comments Accepted to ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena

Provably Efficient Imitation Learning from Observation Alone

Wen Sun, Anirudh Vemula, Byron Boots, J. Andrew Bagnell

Comments ICML 2019

Sum-of-Squares Polynomial Flow

Priyank Jaini, Kira A. Selby, Yaoliang Yu

Comments 13 pages, ICML'2019

Scalable Fair Clustering

Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner

Comments ICML 2019

Complexity of Linear Regions in Deep Networks

Boris Hanin, David Rolnick

Comments ICML 2019

Sorting out Lipschitz function approximation

Cem Anil, James Lucas, Roger Grosse

Comments 8 main pages, 21 pages total, 17 figures. Accepted at ICML 2019

Guided evolutionary strategies: Augmenting random search with surrogate gradients

Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein

Comments Published at ICML 2019

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions

Antoine Liutkus, Umut Şimşekli, Szymon Majewski, Alain Durmus, Fabian-Robert Stöter

Comments Published at the International Conference on Machine Learning (ICML) 2019

Self-Supervised Exploration via Disagreement

Deepak Pathak, Dhiraj Gandhi, Abhinav Gupta

Comments Accepted at ICML 2019. Website at https://pathak22.github.io/exploration-by-disagreement/

Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models

Krishna Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram

Comments 4 pages, CodML workshop at International Conference on Machine Learning (ICML 2019). arXiv admin note: text overlap with arXiv:1904.12222

Scale Steerable Filters for Locally Scale-Invariant Convolutional Neural Networks

Rohan Ghosh, Anupam K. Gupta

Comments Accepted as a Spotlight talk to ICML Workshop on Theoretical Physics for Deep Learning, 2019

Sampling Humans for Optimizing Preferences in Coloring Artwork

Michael McCourt, Ian Dewancker

Comments 6 pages, 4 figures, presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA

Neural Heterogeneous Scheduler

Tegg Taekyong Sung, Valliappa Chockalingam, Alex Yahja, Bo Ryu

Comments 7 pages. The first two authors contributed equally. ICML 2019 Real-world Sequential Decision Making Workshop

Aggregation of pairwise comparisons with reduction of biases

Nadezhda Bugakova, Valentina Fedorova, Gleb Gusev, Alexey Drutsa

Comments presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA

Transfer Learning by Modeling a Distribution over Policies

Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam

Comments Accepted at the ICML 2019 workshop on Multi-Task and Lifelong Reinforcement Learning

Learning Radiative Transfer Models for Climate Change Applications in Imaging Spectroscopy

Shubhankar Deshpande, Brian D. Bue, David R. Thompson, Vijay Natraj, Mario Parente

Comments Accepted to International Conference on Machine Learning (ICML) 2019 Workshop: Climate Change: How Can AI Help?

BayesNAS: A Bayesian Approach for Neural Architecture Search

Hongpeng Zhou, Minghao Yang, Jun Wang, Wei Pan

Comments International Conference on Machine Learning 2019

Making Convolutional Networks Shift-Invariant Again

Richard Zhang

Comments Accepted to ICML 2019

Adversarial camera stickers: A physical camera-based attack on deep learning systems

Juncheng Li, Frank R. Schmidt, J. Zico Kolter

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3896-3904, 2019

Feature-Critic Networks for Heterogeneous Domain Generalization

Yiying Li, Yongxin Yang, Wei Zhou, Timothy M. Hospedales

Comments Presented at ICML 2019

Journal ref Proceedings of the 36th International Conference on Machine Learning, Long Beach, California, PMLR 97, 2019

Dynamic Measurement Scheduling for Event Forecasting using Deep RL

Chun-Hao Chang, Mingjie Mai, Anna Goldenberg

Comments ICML 2019

Bilinear Bandits with Low-rank Structure

Kwang-Sung Jun, Rebecca Willett, Stephen Wright, Robert Nowak

Comments Accepted to ICML'19

Understanding the impact of entropy on policy optimization

Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi, Dale Schuurmans

Comments Accepted to ICML 2019

Fast Context Adaptation via Meta-Learning

Luisa M Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson

Comments Published at the International Conference on Machine Learning (ICML) 2019