ICML

On Catastrophic Forgetting and Mode Collapse in Generative Adversarial Networks

Hoang Thanh-Tung, Truyen Tran

Comments This is an extended version of our paper in ICML'18 Workshop on Theoretical Foundation and Applications of Deep Generative Models. Accepted to IJCNN 2020

Interference and Generalization in Temporal Difference Learning

Emmanuel Bengio, Joelle Pineau, Doina Precup

Comments Submitted to ICML 2020. 20 pages, 14 figures

Functional Tensors for Probabilistic Programming

Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Du Phan, Jonathan P. Chen

Comments Submitted to ICML 2020

An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods

Sanghyuk Chun, Seong Joon Oh, Sangdoo Yun, Dongyoon Han, Junsuk Choe, Youngjoon Yoo

Comments Accepted at ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning. 7 pages, 1 figure

Deep Gated Networks: A framework to understand training and generalisation in deep learning

Chandrashekar Lakshminarayanan, Amit Vikram Singh

Comments 18 Pages, submitted to ICML, added convnets

Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples

Gail Weiss, Yoav Goldberg, Eran Yahav

Comments Accepted in ICML 2018, (Feb 2020: added link to code, at https://github.com/tech-srl/lstar_extraction )

Journal ref ICML 2018

Topology Distance: A Topology-Based Approach For Evaluating Generative Adversarial Networks

Danijela Horak, Simiao Yu, Gholamreza Salimi-Khorshidi

Comments Submitted to ICML 2020; 12 pages, 7 figures

Adaptive Partitioning for Template Functions on Persistence Diagrams

Sarah Tymochko, Elizabeth Munch, Firas A. Khasawneh

Comments To appear in proceedings of IEEE ICMLA 2019

Journal ref 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)

TarMAC: Targeted Multi-Agent Communication

Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael Rabbat, Joelle Pineau

Comments ICML 2019

Bitwise Neural Networks

Minje Kim, Paris Smaragdis

Comments This paper was presented at the International Conference on Machine Learning (ICML) Workshop on Resource-Efficient Machine Learning, Lille, France, Jul. 6-11, 2015

Journal ref International Conference on Machine Learning (ICML) Workshop on Resource-Efficient Machine Learning, Lille, France, Jul. 6-11, 2015

Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms

Pietro Barbiero, Giovanni Squillero, Alberto Tonda

Comments 9 pages, 3 figures, conference. Submitted to ICML 2020

On the Complexity of Approximating Wasserstein Barycenter

Alexey Kroshnin, Darina Dvinskikh, Pavel Dvurechensky, Alexander Gasnikov, Nazarii Tupitsa, Cesar Uribe

Comments Corrected misprints. Added a reference to accelerated Iterative Bregman Projections introduced in arXiv:1906.03622

Journal ref ICML 2019, in PMLR 97:3530-3540. http://proceedings.mlr.press/v97/kroshnin19a.html

R-MADDPG for Partially Observable Environments and Limited Communication

Rose E. Wang, Michael Everett, Jonathan P. How

Comments Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019

Journal ref Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019

Asynchronous Stochastic Gradient Descent with Delay Compensation

Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhi-Ming Ma, Tie-Yan Liu

Comments 20 pages, 5 figures

Journal ref International Conference on Machine Learning. 2017: 4120-4129

A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations

Weili Nie, Yang Zhang, Ankit Patel

Comments 21 pages, ICML 2018 (We revised the proofs of Theorem 1 and 2 in Appendix)

FiniteNet: A Fully Convolutional LSTM Network Architecture for Time-Dependent Partial Differential Equations

Ben Stevens, Tim Colonius

Comments 8 pages, 12 figures. Under review for ICML 2020

Aligning the Pretraining and Finetuning Objectives of Language Models

Nuo Wang Pierse, Jingwen Lu

Comments 8 pages, 2 figures and 6 tables. Submitted to ICML 2020

Revisiting Meta-Learning as Supervised Learning

Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark Campbell, Kilian Q. Weinberger

Comments An extended version of the paper titled "A Meta Understanding of Meta-Learning" presented in ICML 2019 Workshop on Adaptive and Multitask Learning: Algorithms & Systems

Learning Novel Policies For Tasks

Yunbo Zhang, Wenhao Yu, Greg Turk

Comments 8 pages, Accepted ICML 2019

Journal ref Proceedings of the 36th International Conference on Machine Learning, 2019

Kernel Selection for Modal Linear Regression: Optimal Kernel and IRLS Algorithm

Ryoya Yamasaki, Toshiyuki Tanaka

Comments 7 pages, 4 figures, published in the proceedings of the 18th IEEE International Conference on Machine Learning and Applications - ICMLA 2019

CSNNs: Unsupervised, Backpropagation-free Convolutional Neural Networks for Representation Learning

Bonifaz Stuhr, Jürgen Brauer

Comments 18 pages,18 figures, Author's extended version of the paper. Final version presented at 18th IEEE International Conference on Machine Learning and Applications (ICMLA). Boca Raton, Florida / USA. 2019

Stagewise Safe Bayesian Optimization with Gaussian Processes

Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue

Comments International Conference on Machine Learning (ICML) 2018

Stochastic Optimization of Plain Convolutional Neural Networks with Simple methods

Yahia Assiri

Comments arXiv admin note: substantial text overlap with arXiv:1708.04552 by other authors

Journal ref 15th International Conference on Machine Learning and Data Mining, MLDM 2019, vol.II, New York, NY, USA, July 20-25, 2019, ibai-publishing, ISSN 1864-9734 ISBN 978-3-942952-63-7, pages(833-844)

Alpha MAML: Adaptive Model-Agnostic Meta-Learning

Harkirat Singh Behl, Atılım Güneş Baydin, Philip H. S. Torr

Comments 6th ICML Workshop on Automated Machine Learning (2019)

Journal ref ICML Workshop on Automated Machine Learning (2019)

Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models

Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

Comments 12 pages + appendix, 10 figures. Appears in Proceedings of the International Conference on Machine Learning (ICML 2019)

Journal ref International Conference on Machine Learning, 4333-4342 (ICML 2019)

Multiplicative Weights Update as a Distributed Constrained Optimization Algorithm: Convergence to Second-order Stationary Points Almost Always

Ioannis Panageas, Georgios Piliouras, Xiao Wang

Comments Appeared in ICML 2019

Discriminative Embeddings of Latent Variable Models for Structured Data

Hanjun Dai, Bo Dai, Le Song

Comments ICML 2016

Inferring Convolutional Neural Networks' accuracies from their architectural characterizations

Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan Miller, Anushree Ghosh

Comments 6 pages, 5 figures, 5 tables, to appear in proceedings of the 18th International Conference on Machine Learning and Applications - ICMLA 2019

Discovering Nonlinear Relations with Minimum Predictive Information Regularization

Tailin Wu, Thomas Breuel, Michael Skuhersky, Jan Kautz

Comments 26 pages, 11 figures; ICML'19 Time Series Workshop

Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment

Sayan Chakraborty, Smit Shah, Kiumars Soltani, Anna Swigart

Comments 6 pages, 7 figures, 2019 18th IEEE International Conference on Machine Learning and Applications (ICMLA)