ICLR

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length

Stanisław Jastrzębski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos Storkey

Journal ref International Conference on Learning Representations (ICLR) 2019

Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing

Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong

Comments ICLR 2020, code is available at this: https://github.com/jjy1994/Certify_Topk

Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification

Bennet Breier, Arno Onken

Comments 18 pages incl. references and appendix, 16 figures, ICLR 2020 Conference

Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model

Wenhan Xiong, Jingfei Du, William Yang Wang, Veselin Stoyanov

Comments Accepted to ICLR 2020

A Constructive Prediction of the Generalization Error Across Scales

Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit

Comments ICLR 2020

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning

Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio

Comments Accepted at ICLR 2019

Wasserstein Auto-Encoders

Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schoelkopf

Comments Published at ICLR 2018.. Included much wider hyperparameter sweep: in significant improvements in FIDs on CelebA

Simulating Execution Time of Tensor Programs using Graph Neural Networks

Jakub M. Tomczak, Romain Lepert, Auke Wiggers

Comments All authors contributed equally. Accepted as a workshop paper at Representation Learning on Graphs and Manifolds @ ICLR 2019. Fixed values in Table 1

Representation Learning with Multisets

Vasco Portilheiro

Comments Under review as a conference paper at ICLR 2020. Preliminary version accepted to the NeurIPS 2019 workshop on Sets and Partitions

An Empirical Study of Example Forgetting during Deep Neural Network Learning

Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon

Comments ICLR 2019

Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach

Rajeev Bhatt Ambati, Saptarashmi Bandyopadhyay, Prasenjit Mitra

Comments Submitted to ICLR 2020

Enhancing Certifiable Robustness via a Deep Model Ensemble

Huan Zhang, Minhao Cheng, Cho-Jui Hsieh

Comments This is an extended version of ICLR 2019 Safe Machine Learning Workshop (SafeML) paper, "RobBoost: A provable approach to boost the robustness of deep model ensemble". May 6, 2019, New Orleans, LA, USA

Noisy Networks for Exploration

Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Ian Osband, Alex Graves, Vlad Mnih, Remi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

Comments ICLR 2018

Label-efficient audio classification through multitask learning and self-supervision

Tyler Lee, Ting Gong, Suchismita Padhy, Andrew Rouditchenko, Anthony Ndirango

Comments Presented at ICLR 2019 Limited Labeled Data (LLD) Workshop

Effective Use of Variational Embedding Capacity in Expressive End-to-End Speech Synthesis

Eric Battenberg, Soroosh Mariooryad, Daisy Stanton, RJ Skerry-Ryan, Matt Shannon, David Kao, Tom Bagby

Comments Submitted to ICLR 2020

A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks

Sanjeev Arora, Nadav Cohen, Noah Golowich, Wei Hu

Comments Published as a conference paper at ICLR 2019

Deep Variational Information Bottleneck

Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy

Comments 19 pages, 8 figures, Accepted to ICLR17

Journal ref Proceedings of the International Conference on Learning Representations (ICLR) 2017

LanczosNet: Multi-Scale Deep Graph Convolutional Networks

Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel

Comments The International Conference on Learning Representations (ICLR) 2019

ProDyn0: Inferring calponin homology domain stretching behavior using graph neural networks

Ali Madani, Cyna Shirazinejad, Jia Rui Ong, Hengameh Shams, Mohammad Mofrad

Comments 8 pages, 2 figures, 2 tables

Journal ref ICLR 2019: Representation learning on graphs and manifolds

Feature-Wise Bias Amplification

Klas Leino, Emily Black, Matt Fredrikson, Shayak Sen, Anupam Datta

Comments Published in ICLR 2019

Learning protein sequence embeddings using information from structure

Tristan Bepler, Bonnie Berger

Comments 17 pages, 3 figures, 8 tables, proceedings of ICLR 2019

Journal ref International Conference on Learning Representations, 2019

IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification

Lin Meng, Jiawei Zhang

Comments 14 pages, 6 figures, submitted to ICLR 2020

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten Borgwardt

Comments Published as a conference paper at ICLR 2019

Benefit of Interpolation in Nearest Neighbor Algorithms

Yue Xing, Qifan Song, Guang Cheng

Comments Under review as a conference paper at ICLR 2020

Adversarially Robust Generalization Just Requires More Unlabeled Data

Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John Hopcroft, Liwei Wang

Comments 16 pages. Submitted to ICLR 2020

Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Penghang Yin, Jiancheng Lyu, Shuai Zhang, Stanley Osher, Yingyong Qi, Jack Xin

Comments in International Conference on Learning Representations (ICLR) 2019

Interpolation-Prediction Networks for Irregularly Sampled Time Series

Satya Narayan Shukla, Benjamin M. Marlin

Comments International Conference on Learning Representations. arXiv admin note: substantial text overlap with arXiv:1812.00531

Adversarial Reprogramming of Neural Networks

Gamaleldin F. Elsayed, Ian Goodfellow, Jascha Sohl-Dickstein

Journal ref International Conference on Learning Representations 2019

A comprehensive, application-oriented study of catastrophic forgetting in DNNs

B. Pfülb, A. Gepperth

Comments 14 pages, 12 + 23 figures, ICLR | 2019 Seventh International Conference on Learning Representations

Journal ref ICLR 2019 International Conference on Learning Representations

ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks

Mingzhang Yin, Mingyuan Zhou

Comments ICLR 2019