ICML

Improving Neural Language Modeling via Adversarial Training

Dilin Wang, Chengyue Gong, Qiang Liu

Journal ref International Conference on Machine Learning 2019

Explaining Deep Classification of Time-Series Data with Learned Prototypes

Alan H. Gee, Diego Garcia-Olano, Joydeep Ghosh, David Paydarfar

Comments The first two authors contributed equally. Accepted May 20, Presented Jun 14, 2019 at the ICML Time-series Workshop in Long Beach, CA, USA. Accepted June 15, Presented Aug 11, 2019 at the IJCAI Workshop on Knowledge Discovery in Healthcare Data in Macao, China. Formal proceedings available in the CEUR Workshop Proceedings (http://ceur-ws.org/Vol-2429/)

Journal ref Proceedings of the 4th International Workshop on Knowledge Discovery in Healthcare Data, co-located with the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019)

Exploration Conscious Reinforcement Learning Revisited

Lior Shani, Yonathan Efroni, Shie Mannor

Comments Published @ICML 2019 (36th International Conference on Machine Learning 2019)

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5680-5689, 2019

Rates of Convergence for Sparse Variational Gaussian Process Regression

David R. Burt, Carl E. Rasmussen, Mark van der Wilk

Comments International Conference on Machine Learning (ICML 2019)

On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points

Chi Jin, Praneeth Netrapalli, Rong Ge, Sham M. Kakade, Michael I. Jordan

Comments A preliminary version of this paper, with a subset of the results that are presented here, was presented at ICML 2017 (also as arXiv:1703.00887)

Detecting Compromised Implicit Association Test Results Using Supervised Learning

Brendon Boldt, Zack While, Eric Breimer

Comments 6 pages, 1 figure

Journal ref 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), Orlando, FL, 2018, pp. 449-453

Subspace Robust Wasserstein Distances

François-Pierre Paty, Marco Cuturi

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5072-5081, 2019

Early Classification for Agricultural Monitoring from Satellite Time Series

Marc Rußwurm, Romain Tavenard, Sébastien Lefèvre, Marco Körner

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

Finite size corrections for neural network Gaussian processes

Joseph M. Antognini

Comments Presented at the 2019 ICML Workshop on Theoretical Physics for Deep Learning

Utilizing Eye Gaze to Enhance the Generalization of Imitation Networks to Unseen Environments

Congcong Liu, Yuying Chen, Lei Tai, Ming Liu, Bertram Shi

Comments 4 pages, 3 figures, accepted by ICML 2019 Workshop on Understanding and Improving Generalization in Deep Learning

Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap

Edwin Fong, Simon Lyddon, Chris Holmes

Comments Accepted at International Conference on Machine Learning (ICML) 2019

Multivariate Submodular Optimization

Richard Santiago, F. Bruce Shepherd

Comments arXiv admin note: text overlap with arXiv:1803.03767

Journal ref Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97:5599-5609, 2019

Iterative Linearized Control: Stable Algorithms and Complexity Guarantees

Vincent Roulet, Siddhartha Srinivasa, Dmitriy Drusvyatskiy, Zaid Harchaoui

Comments Short version appeared in International Conference on Machine Learning (ICML) 2019

Analysis of Memory Capacity for Deep Echo State Networks

Xuanlin Liu, Mingzhe Chen, Changchuan Yin, Walid Saad

Comments 6 pages, 8 figures, Published in 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)

Predicting Actions to Help Predict Translations

Zixiu Wu, Julia Ive, Josiah Wang, Pranava Madhyastha, Lucia Specia

Comments Accepted to workshop "The How2 Challenge: New Tasks for Vision & Language" of International Conference on Machine Learning 2019

Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances

Bugra Can, Mert Gurbuzbalaban, Lingjiong Zhu

Comments 72 pages

Journal ref International Conference on Machine Learning 2019, 891-901

Transparency: Motivations and Challenges

Adrian Weller

Comments Updated article based on the paper presented at 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017), Sydney, NSW, Australia

Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts

Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama

Comments 9 pages, 3 figures, 3 tables. Accepted at ICML 2019

Neurally-Guided Structure Inference

Sidi Lu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu

Comments Proceedings of the 36th International Conference on Machine Learning (ICML 2019). First two authors contributed equally. Project page: http://ngsi.csail.mit.edu

Journal ref PMLR(2019)97: 4144--4153

Simple Black-box Adversarial Attacks

Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger

Comments Published at ICML 2019

Variational inference for neural network matrix factorization and its application to stochastic blockmodeling

Onno Kampman, Creighton Heaukulani

Comments In proceedings of the 2019 ICML Workshop on Learning and Reasoning with Graph-Structured Representations, Long Beach, USA

Interpretable Encrypted Searchable Neural Networks

Kai Chen, Zhongrui Lin, Jian Wan, Chungen Xu

Comments The Second International Conference on Machine Learning for Cyber Security (ML4CS 2019). Keyword: Searchable Encryption; Searchable Neural Networks; Probabilistic Learning; Adversarial Learning; Automatic Weight Update

Off-Policy Deep Reinforcement Learning without Exploration

Scott Fujimoto, David Meger, Doina Precup

Comments ICML 2019

An Extensible Interactive Interface for Agent Design

Matthew Rahtz, James Fang, Anca D. Dragan, Dylan Hadfield-Menell

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

Recursive Sketches for Modular Deep Learning

Badih Ghazi, Rina Panigrahy, Joshua R. Wang

Comments Published in ICML 2019

Sparsity Emerges Naturally in Neural Language Models

Naomi Saphra, Adam Lopez

Comments Published in the ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena: https://openreview.net/forum?id=H1ets1h56E

Learning to Optimize Multigrid PDE Solvers

Daniel Greenfeld, Meirav Galun, Ron Kimmel, Irad Yavneh, Ronen Basri

Comments Proceedings of the 36th International Conference on Machine Learning (ICML 2019)

Submodular Cost Submodular Cover with an Approximate Oracle

Victoria G. Crawford, Alan Kuhnle, My T. Thai

Comments International Conference on Machine Learning. 2019

Combating Label Noise in Deep Learning Using Abstention

Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof

Comments ICML 2019. Added source code link

Temporal Gaussian Mixture Layer for Videos

AJ Piergiovanni, Michael S. Ryoo

Comments ICML 2019