ICML

Nonparametric Bayesian Deep Networks with Local Competition

Konstantinos P. Panousis, Sotirios Chatzis, Sergios Theodoridis

Comments Proc. ICML 2019

Learning to Reweight Examples for Robust Deep Learning

Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun

Comments 13 pages; Published at ICML 2018; Code released at: https://github.com/uber-research/learning-to-reweight-examples

On the Universality of Invariant Networks

Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman

Comments ICML 2019

Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM

Sheng Lin, Xiaolong Ma, Shaokai Ye, Geng Yuan, Kaisheng Ma, Yanzhi Wang

Comments Accepted by ICML workshop (ODML-CDNNR2019). arXiv admin note: substantial text overlap with arXiv:1903.09769

ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning

Xiaolong Ma, Geng Yuan, Sheng Lin, Zhengang Li, Hao Sun, Yanzhi Wang

Comments Submitted to ICML workshop

Information-Theoretic Considerations in Batch Reinforcement Learning

Jinglin Chen, Nan Jiang

Comments Published in ICML 2019

Model Comparison for Semantic Grouping

Francisco Vargas, Kamen Brestnichki, Nils Hammerla

Comments Proceedings of the 36th International Conference on Machine Learning

Categorical Feature Compression via Submodular Optimization

MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, Afshin Rostamizadeh

Comments Accepted to ICML 2019. Authors are listed in alphabetical order

Context-Aware Zero-Shot Learning for Object Recognition

Eloi Zablocki, Patrick Bordes, Benjamin Piwowarski, Laure Soulier, Patrick Gallinari

Comments Accepted at ICML 2019

Domain Agnostic Learning with Disentangled Representations

Xingchao Peng, Zijun Huang, Ximeng Sun, Kate Saenko

Journal ref Proceedings of the 36th International Conference on Machine Learning, Long Beach, California, PMLR 97, 2019

End-to-End Probabilistic Inference for Nonstationary Audio Analysis

William J. Wilkinson, Michael Riis Andersen, Joshua D. Reiss, Dan Stowell, Arno Solin

Comments Accepted to the Thirty-sixth International Conference on Machine Learning (ICML) 2019

Recognition of Acoustic Events Using Masked Conditional Neural Networks

Fady Medhat, David Chesmore, John Robinson

Comments Restricted Boltzmann Machine, RBM, Conditional Restricted Boltzmann Machine, CRBM, Conditional Neural Networks, CLNN, Masked Conditional Neural Networks, MCLNN, Deep Neural Network, Environmental Sound Recognition, ESR

Journal ref IEEE International Conference on Machine Learning and Applications (ICMLA) Year: 2017 Pages: 199 - 206

Bayesian Generative Active Deep Learning

Toan Tran, Thanh-Toan Do, Ian Reid, Gustavo Carneiro

Comments Accepted to ICML 2019

Composable Planning with Attributes

Amy Zhang, Adam Lerer, Sainbayar Sukhbaatar, Rob Fergus, Arthur Szlam

Journal ref International Conference on Machine Learning, 2018

Neural Collaborative Subspace Clustering

Tong Zhang, Pan Ji, Mehrtash Harandi, Wenbing Huang, Hongdong Li

Comments Accepted to ICML 2019

Submodular Maximization Beyond Non-negativity: Guarantees, Fast Algorithms, and Applications

Christopher Harshaw, Moran Feldman, Justin Ward, Amin Karbasi

Comments submitted to ICML 2019

Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors

Gintare Karolina Dziugaite, Daniel M. Roy

Comments 18 pages, 6 figures; combines ICML camera ready with supplementary materials

Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1377-1386, 2018

Convolutional Networks for Spherical Signals

Taco Cohen, Mario Geiger, Jonas Köhler, Max Welling

Journal ref Principled Approaches to Deep Learning Workshop, ICML 2017

Harmonic Exponential Families on Manifolds

Taco S. Cohen, Max Welling

Comments fixed typo

Journal ref Proceedings of the International Conference on Machine Learning, 2015

Learning the Irreducible Representations of Commutative Lie Groups

Taco Cohen, Max Welling

Journal ref Proceedings of the International Conference on Machine Learning, 2014

A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models

Beilun Wang, Arshdeep Sekhon, Yanjun Qi

Comments ICML 2018; Proof and Design of W in Appendix; Available as R tool "jeek". This updated version correct a few equation errors

Journal ref International Conference on Machine Learning. 2018

Programmatically Interpretable Reinforcement Learning

Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri

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

Journal ref PMLR 80:5045-5054

Clique pooling for graph classification

Enxhell Luzhnica, Ben Day, Pietro Lio'

Comments Under review as a workshop paper at RLGM 2019 @ ICML

High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach

Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely

Journal ref Proceedings of the 35th International Conference on Machine Learning, 2018

Asymmetric Valleys: Beyond Sharp and Flat Local Minima

Haowei He, Gao Huang, Yang Yuan

Comments submitted to ICML 2019

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory Sayres

Journal ref ICML 2018

There are No Bit Parts for Sign Bits in Black-Box Attacks

Abdullah Al-Dujaili, Una-May O'Reilly

Comments Added results of Ensemble Adv Learning. ICML template

NetGAN: Generating Graphs via Random Walks

Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann

Comments ICML 2018

Journal ref Proceedings of the 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden, pp. 609-618

Image Based Fashion Product Recommendation with Deep Learning

Hessel Tuinhof, Clemens Pirker, Markus Haltmeier

Journal ref LOD: International Conference on Machine Learning, Optimization, and Data Science Machine Learning, Optimization, and Data Science 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers

meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting

Xu Sun, Xuancheng Ren, Shuming Ma, Houfeng Wang

Comments Accepted by the 34th International Conference on Machine Learning (ICML 2017)