ICML

A Contrastive Divergence for Combining Variational Inference and MCMC

Francisco J. R. Ruiz, Michalis K. Titsias

Comments International Conference on Machine Learning (ICML 2019). 12 pages, 3 figures

AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs

Gabriele Abbati, Philippe Wenk, Michael A Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer

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

Low-Complexity Data-Parallel Earth Mover's Distance Approximations

Kubilay Atasu, Thomas Mittelholzer

Comments To appear in ICML 2019: http://proceedings.mlr.press/v97/atasu19a.html

Variational Implicit Processes

Chao Ma, Yingzhen Li, José Miguel Hernández-Lobato

Comments ICML 2019 camera-ready version

Two-level Explanations in Music Emotion Recognition

Verena Haunschmid, Shreyan Chowdhury, Gerhard Widmer

Comments ML4MD Workshop of the 36th International Conference on Machine Learning

LatentGNN: Learning Efficient Non-local Relations for Visual Recognition

Songyang Zhang, Shipeng Yan, Xuming He

Comments ICML 2019

Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact

Kush R. Varshney, Aleksandra Mojsilovic

Comments appearing at the 2019 ICML AI for Social Good Workshop

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations

Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer

Comments ICML 2019 [full oral]. arXiv admin note: text overlap with arXiv:1805.08394

HexaGAN: Generative Adversarial Nets for Real World Classification

Uiwon Hwang, Dahuin Jung, Sungroh Yoon

Comments Accepted to ICML 2019

Policy Certificates: Towards Accountable Reinforcement Learning

Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill

Comments article appearing at ICML 2019; full version including appendix

Actor-Attention-Critic for Multi-Agent Reinforcement Learning

Shariq Iqbal, Fei Sha

Comments ICML 2019 camera ready version

Learning Optimal Fair Policies

Razieh Nabi, Daniel Malinsky, Ilya Shpitser

Journal ref The Thirty-sixth International Conference on Machine Learning (ICML 2019)

Dirichlet Simplex Nest and Geometric Inference

Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen

Comments ICML 2019

Learning to Route in Similarity Graphs

Dmitry Baranchuk, Dmitry Persiyanov, Anton Sinitsin, Artem Babenko

Comments Published in ICML 2019

Scalable Training of Inference Networks for Gaussian-Process Models

Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu

Comments ICML 2019. Update results added in the camera-ready version

Identity Connections in Residual Nets Improve Noise Stability

Shuzhi Yu, Carlo Tomasi

Comments ICML 2019 Workshop on Understanding and Improving Generalization in Deep Learning, additional analysis on a property called Dominant Gradient Flow of Residual Nets in Appendix D

Using Deep Networks and Transfer Learning to Address Disinformation

Numa Dhamani, Paul Azunre, Jeffrey L. Gleason, Craig Corcoran, Garrett Honke, Steve Kramer, Jonathon Morgan

Comments AI for Social Good Workshop at the International Conference on Machine Learning, Long Beach, United States (2019)

Sublinear quantum algorithms for training linear and kernel-based classifiers

Tongyang Li, Shouvanik Chakrabarti, Xiaodi Wu

Comments 31 pages, 1 figure

Journal ref Proceedings of the 36th International Conference on Machine Learning (ICML 2019), PMLR 97:3815-3824, 2019

Separating value functions across time-scales

Joshua Romoff, Peter Henderson, Ahmed Touati, Emma Brunskill, Joelle Pineau, Yann Ollivier

Comments Full version accepted to ICML 2019. Extended abstract also to be presented at RLDM 2019

Equivariant Transformer Networks

Kai Sheng Tai, Peter Bailis, Gregory Valiant

Comments ICML 2019

Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruosong Wang

Comments In ICML 2019

Width Provably Matters in Optimization for Deep Linear Neural Networks

Simon S. Du, Wei Hu

Comments In ICML 2019

A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation

Ramin Raziperchikolaei, Harish S. Bhat

Comments 18 pages, ICML 2019

Journal ref PMLR 97:5380-5388, 2019

Safe Grid Search with Optimal Complexity

Eugene Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi

Journal ref International Conference on Machine Learning, 2019

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks

Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh

Comments ICML 2019

Adversarial Attacks on Node Embeddings via Graph Poisoning

Aleksandar Bojchevski, Stephan Günnemann

Comments ICML 2019, PMLR 97:695-704

Fingerprint Policy Optimisation for Robust Reinforcement Learning

Supratik Paul, Michael A. Osborne, Shimon Whiteson

Comments ICML 2019

Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time

Asish Ghoshal, Jean Honorio

Comments Accepted to ICML 2018

Journal ref International Conference on Machine Learning (ICML), 2018

Are Generative Classifiers More Robust to Adversarial Attacks?

Yingzhen Li, John Bradshaw, Yash Sharma

Comments ICML 2019

Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data

Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant

Comments Updates for ICML'19 camera-ready