ICML

Towards Black-box Iterative Machine Teaching

Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song

Comments Published in ICML 2018

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Irina Higgins, Arka Pal, Andrei A. Rusu, Loic Matthey, Christopher P Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner

Comments ICML 2017

The Shattered Gradients Problem: If resnets are the answer, then what is the question?

David Balduzzi, Marcus Frean, Lennox Leary, JP Lewis, Kurt Wan-Duo Ma, Brian McWilliams

Comments ICML 2017, final version

Journal ref PMLR volume 70 (2017)

Strongly-Typed Agents are Guaranteed to Interact Safely

David Balduzzi

Comments ICML 2017, final version

Journal ref PMLR volume 70, 2017

Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks

David Balduzzi, Brian McWilliams, Tony Butler-Yeoman

Comments ICML 2017, final version

Journal ref PMLR volume 70, 2017

Learning Representations for Counterfactual Inference

Fredrik D. Johansson, Uri Shalit, David Sontag

Comments Appeared in ICML 2016

Mix&Match - Agent Curricula for Reinforcement Learning

Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Simon Osindero, Nicolas Heess, Razvan Pascanu

Comments ICML 2018

Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning

Thomas G. Dietterich, George Trimponias, Zhitang Chen

Comments To appear at ICML 2018

Composite Marginal Likelihood Methods for Random Utility Models

Zhibing Zhao, Lirong Xia

Comments 22 pages, 3 figures, accepted by ICML 2018

Graph networks as learnable physics engines for inference and control

Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin Riedmiller, Raia Hadsell, Peter Battaglia

Comments ICML 2018

On the Limitations of First-Order Approximation in GAN Dynamics

Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt

Comments 18 pages, 4 figures, accepted to ICML 2018

Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression

Haitao Liu, Jianfei Cai, Yi Wang, Yew-Soon Ong

Comments paper + supplementary material, appears in Proceedings of ICML 2018

Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit

Sreejith Kallummil, Sheetal Kalyani

Comments Accepted in ICML 2018. Significantly improved and extended version of arXiv preprint arXiv:1707.08712

Binary Classification with Karmic, Threshold-Quasi-Concave Metrics

Bowei Yan, Oluwasanmi Koyejo, Kai Zhong, Pradeep Ravikumar

Comments ICML 2018

Topological mixture estimation

Steve Huntsman

Comments 10 pages, 10 figures, accepted to ICML 2018

Invariance of Weight Distributions in Rectified MLPs

Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher

Comments ICML 2018

Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization

Louis Filstroff, Alberto Lumbreras, Cédric Févotte

Comments Accepted for publication at ICML 2018

Differentially Private Database Release via Kernel Mean Embeddings

Matej Balog, Ilya Tolstikhin, Bernhard Schölkopf

Comments 35th International Conference on Machine Learning (ICML 2018)

Privacy Aware Offloading of Deep Neural Networks

Sam Leroux, Tim Verbelen, Pieter Simoens, Bart Dhoedt

Comments ICML 2018 Privacy in Machine Learning and Artificial Intelligence workshop

A Progressive Batching L-BFGS Method for Machine Learning

Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang

Comments ICML 2018. 25 pages, 17 figures, 2 tables

Semi-Implicit Variational Inference

Mingzhang Yin, Mingyuan Zhou

Comments ICML 2018

Neural Inverse Rendering for General Reflectance Photometric Stereo

Tatsunori Taniai, Takanori Maehara

Comments To appear in International Conference on Machine Learning 2018 (ICML 2018). 10 pages + 20 pages (appendices)

Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent

Trevor Campbell, Tamara Broderick

Comments Appearing in the 2018 International Conference on Machine Learning (ICML). 13 pages, 7 figures

Overcoming catastrophic forgetting with hard attention to the task

Joan Serrà, Dídac Surís, Marius Miron, Alexandros Karatzoglou

Comments Includes appendix. Accepted for ICML 2018

Importance Weighted Transfer of Samples in Reinforcement Learning

Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta, Marcello Restelli

Comments Accepted at ICML 2018

Understanding Generalization and Optimization Performance of Deep CNNs

Pan Zhou, Jiashi Feng

Comments This paper was accepted by ICML. It has 38 pages

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations

Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman, Evgeny Andriyash

Comments Published as a conference paper at International Conference on Machine Learning (ICML), 2018

Inference Suboptimality in Variational Autoencoders

Chris Cremer, Xuechen Li, David Duvenaud

Comments ICML

Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication

Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian

Comments Accepted to ICML 2018

Coordinated Multi-Agent Imitation Learning

Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey

Comments International Conference on Machine Learning 2017

Journal ref Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey ; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1995-2003, 2017