ICML

Particle Flow Bayes' Rule

Xinshi Chen, Hanjun Dai, Le Song

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1022-1031, 2019

Generative Adversarial User Model for Reinforcement Learning Based Recommendation System

Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1052-1061, 2019

World Programs for Model-Based Learning and Planning in Compositional State and Action Spaces

Marwin H. S. Segler

Comments Accepted at the Generative Modeling and Model-Based Reasoning for Robotics and AI workshop at ICML 2019. Presented on June 14th 2019. See https://sites.google.com/view/mbrl-icml2019

Journal ref https://sites.google.com/view/mbrl-icml2019

Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension

Jisu Kim, Jaehyeok Shin, Alessandro Rinaldo, Larry Wasserman

Comments 51 pages, to be published in Proceedings of Thirty-sixth International Conference on Machine Learning (ICML 2019), Volume 97, 2019

Towards Building a Real Time Mobile Device Bird Counting System Through Synthetic Data Training and Model Compression

Runde Yang

Comments The paper is in a wrong format for ICML. I really need to withdraw the paper to modify the content and submit it to other computer vision conferences. Some sections need to be completely rewritten and I recognize certain parts that are not consistent with the major theme of the paper

Analyzing Utility of Visual Context in Multimodal Speech Recognition Under Noisy Conditions

Tejas Srinivasan, Ramon Sanabria, Florian Metze

Comments Accepted to How2 Workshop, ICML 2019

Colorectal Polyp Segmentation by U-Net with Dilation Convolution

Xinzi Sun, Pengfei Zhang, Dechun Wang, Yu Cao, Benyuan Liu

Comments 8 pages. ICMLA (International Conference on Machine Learning and Applications)

ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables

Mingzhang Yin, Yuguang Yue, Mingyuan Zhou

Comments Published in ICML 2019. We have updated Section 4.2 and the Appendix to reflect the improvements brought by fixing some bugs hidden in our original code. Please find the Errata in the authors' websites and check the updated code in Github

An Application of Generative Adversarial Networks for Super Resolution Medical Imaging

Rewa Sood, Binit Topiwala, Karthik Choutagunta, Rohit Sood, Mirabela Rusu

Comments International Conference on Machine Learning Applications, 6 pages, 5 figures, 2 tables

Journal ref 17th IEEE International Conference on Machine Learning and Applications,2018, pp. 326-331

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

M. Baity-Jesi, L. Sagun, M. Geiger, S. Spigler, G. Ben Arous, C. Cammarota, Y. LeCun, M. Wyart, G. Biroli

Comments 10 pages, 5 figures. Version accepted at ICML 2018

Journal ref PMLR 80:324-333, 2018; Republication with DOI (cite this one): J. Stat. Mech. (2019) 124013

Model Weight Theft With Just Noise Inputs: The Curious Case of the Petulant Attacker

Nicholas Roberts, Vinay Uday Prabhu, Matthew McAteer

Comments Presented at the Security and Privacy of Machine Learning Workshop, 36th International Conference on Machine Learning (ICML 2019), Long Beach, California, USA

An Adaptive Deep Learning Algorithm Based Autoencoder for Interference Channels

Dehao Wu, Maziar Nekovee, Yue Wang

Comments 6 pages, 10 figures, 2nd MLN 2019 accepted

Journal ref 2nd IFIP International Conference on Machine Learning for Networking 2019

More Efficient Off-Policy Evaluation through Regularized Targeted Learning

Aurélien F. Bibaut, Ivana Malenica, Nikos Vlassis, Mark J. van der Laan

Comments We are uploading the full paper with the appendix as of 12/12/2019, as we noticed that, unlike the main text, the appendix has not been made available on PMLR's website. The version of the appendix in this document is the same that we have been sending by email since June 2019 to readers who solicited it

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:654-663, 2019

Bayesian Model Selection for Change Point Detection and Clustering

Othmane Mazhar, Cristian R. Rojas, Carlo Fischione, Mohammad R. Hesamzadeh

Comments 37 page, 4 figures, Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80:3433-3442, 2018

The Variational Predictive Natural Gradient

Da Tang, Rajesh Ranganath

Comments International Conference on Machine Learning (ICML), 2019

Crawling in Rogue's dungeons with (partitioned) A3C

Andrea Asperti, Daniele Cortesi, Francesco Sovrano

Comments Accepted at the Fourth International Conference on Machine Learning, Optimization, and Data Science (LOD 2018)

Detecting anthropogenic cloud perturbations with deep learning

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony Caterini, Dino Sejdinovic, Philip Stier

Comments Awarded Best Paper and Spotlight Oral at Climate Change: How Can AI Help? (Workshop) at International Conference on Machine Learning (ICML), Long Beach, California, 2019

Geometric Scattering for Graph Data Analysis

Feng Gao, Guy Wolf, Matthew Hirn

Journal ref Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2122-2131, 2019

GDPP: Learning Diverse Generations Using Determinantal Point Process

Mohamed Elfeki, Camille Couprie, Morgane Riviere, Mohamed Elhoseiny

Journal ref International Conference on Machine Learning 2019

Analyzing Federated Learning through an Adversarial Lens

Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, Seraphin Calo

Comments Extended version of paper accepted to ICML 2019, code available at https://github.com/inspire-group/ModelPoisoning; 19 pages, 14 figures

Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing

Davide Bacciu, Federico Errica, Alessio Micheli

Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80 (2018) 294-303

Band-limited Training and Inference for Convolutional Neural Networks

Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron Elmore, Michael Franklin

Comments Published at International Conference on Machine Learning (ICML)

Complementary-Label Learning for Arbitrary Losses and Models

Takashi Ishida, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama

Comments accepted to ICML 2019 (Added errata on Nov. 19, 2019)

Graph Element Networks: adaptive, structured computation and memory

Ferran Alet, Adarsh K. Jeewajee, Maria Bauza, Alberto Rodriguez, Tomas Lozano-Perez, Leslie Pack Kaelbling

Comments Accepted to ICML 2019

Hierarchically Structured Meta-learning

Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li

Comments ICML 2019; Errata: this version fix the results of A1 in Table 10

Visualizing and Understanding Self-attention based Music Tagging

Minz Won, Sanghyuk Chun, Xavier Serra

Comments Machine Learning for Music Discovery Workshop (ML4MD) at ICML 2019

A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music

Adam Roberts, Jesse Engel, Colin Raffel, Curtis Hawthorne, Douglas Eck

Comments ICML Camera Ready Version (w/ fixed typos)

Journal ref ICML 2018

Collapse Resistant Deep Convolutional GAN for Multi-Object Image Generation

Elijah D. Bolluyt, Cristina Comaniciu

Comments Accepted to IEEE International Conference on Machine Learning and Applications 2019

Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem

Sergey Pavlov, Alexey Artemov, Maksim Sharaev, Alexander Bernstein, Evgeny Burnaev

Comments Accepted to IEEE International Conference on Machine Learning and Applications (ICMLA 2019). Typos corrected, images updated

Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders

Matteo Manica, Ali Oskooei, Jannis Born, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez

Comments 11 pages, 5 figures, 1 table, Workshop on Computational Biology at the International Conference on Machine Learning (ICML), Long Beach, CA, 2019

Journal ref Mol. Pharmaceutics 2019