ICLR

Data Interpolating Prediction: Alternative Interpretation of Mixup

Takuya Shimada, Shoichiro Yamaguchi, Kohei Hayashi, Sosuke Kobayashi

Comments Presented at the 2nd Learning from Limited Labeled Data (LLD) Workshop at ICLR 2019

Predicting the Generalization Gap in Deep Networks with Margin Distributions

Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio

Comments Published in ICLR 2019

Learning what and where to attend

Drew Linsley, Dan Shiebler, Sven Eberhardt, Thomas Serre

Comments Previously called Global-and-local attention networks for visual recognition. Current version published in ICLR 2019: https://openreview.net/forum?id=BJgLg3R9KQ

Maximum Weighted Loss Discrepancy

Fereshte Khani, Aditi Raghunathan, Percy Liang

Comments ICLR 2019 Workshop. Safe Machine Learning: Specification, Robustness, and Assurance

Unsupervised Hyperalignment for Multilingual Word Embeddings

Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin

Comments ICLR 2019

Passage Ranking with Weak Supervision

Peng Xu, Xiaofei Ma, Ramesh Nallapati, Bing Xiang

Comments 6 pages, 1 figure

Journal ref ICLR 2019 LLD workshop

Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience

Vaishnavh Nagarajan, J. Zico Kolter

Comments Published as a conference paper at ICLR 2019

Efficiently testing local optimality and escaping saddles for ReLU networks

Chulhee Yun, Suvrit Sra, Ali Jadbabaie

Comments 23 pages, appeared at ICLR 2019

Small nonlinearities in activation functions create bad local minima in neural networks

Chulhee Yun, Suvrit Sra, Ali Jadbabaie

Comments 33 pages, appeared at ICLR 2019

A Knowledge Graph-based Approach for Exploring the U.S. Opioid Epidemic

Maulik R. Kamdar, Tymor Hamamsy, Shea Shelton, Ayin Vala, Tome Eftimov, James Zou, Suzanne Tamang

Comments 4 pages, 2 figures, ICLR AI for social good workshop 2019

Consequentialist conditional cooperation in social dilemmas with imperfect information

Alexander Peysakhovich, Adam Lerer

Journal ref Proceedings of the International Conference on Learning Representations 2018

A Direct Approach to Robust Deep Learning Using Adversarial Networks

Huaxia Wang, Chun-Nam Yu

Comments 15 pages

Journal ref ICLR 2019

Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification

Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap, Mihail Douhaniaris, Preethi Seshadri, John Whaley

Comments Published as a workshop paper at ICLR 2019 (DeepGenStruct-2019)

Inferring Javascript types using Graph Neural Networks

Jessica Schrouff, Kai Wohlfahrt, Bruno Marnette, Liam Atkinson

Comments Published at the Representation Learning on Graphs and Manifolds ICLR 2019 workshop (https://rlgm.github.io/papers/)

What do you learn from context? Probing for sentence structure in contextualized word representations

Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R. Bowman, Dipanjan Das, Ellie Pavlick

Comments ICLR 2019 camera-ready version, 17 pages including appendices

Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference

Lukas Galke, Iacopo Vagliano, Ansgar Scherp

Comments 5 pages, 1 figure, Representation Learning on Graphs and Manifolds Workshop of the International Conference on Learning Representations (ICLR), 2019

Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum

Comments Published at ICLR 2019

Structured Prediction using cGANs with Fusion Discriminator

Faisal Mahmood, Wenhao Xu, Nicholas J. Durr, Jeremiah W. Johnson, Alan Yuille

Comments 13 pages, 5 figures, 3 tables

Journal ref Workshop on Deep Generative Models for Structured Prediction at ICLR 2019

Learning To Simulate

Nataniel Ruiz, Samuel Schulter, Manmohan Chandraker

Comments Published at International Conference on Learning Representations (ICLR) 2019

Learning Factorized Multimodal Representations

Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency, Ruslan Salakhutdinov

Comments ICLR 2019

Disentangling Content and Style via Unsupervised Geometry Distillation

Wayne Wu, Kaidi Cao, Cheng Li, Chen Qian, Chen Change Loy

Comments Accepted to ICLR 2019 Workshop

Variational Recurrent Neural Networks for Graph Classification

Edouard Pineau, Nathan de Lara

Comments Representation Learning on Graphs and Manifolds workshop, ICLR 2019

Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering

Victor Zhong, Caiming Xiong, Nitish Shirish Keskar, Richard Socher

Comments ICLR 2019; 9 pages, 7 figures

Exploring the Hyperparameter Landscape of Adversarial Robustness

Evelyn Duesterwald, Anupama Murthi, Ganesh Venkataraman, Mathieu Sinn, Deepak Vijaykeerthy

Journal ref Safe Machine Learning Workshop at ICLR (International Conference on Learning Representations), 2019

Interactive Image Generation Using Scene Graphs

Gaurav Mittal, Shubham Agrawal, Anuva Agarwal, Sushant Mehta, Tanya Marwah

Comments Published at ICLR 2019 Deep Generative Models for Highly Structured Data Workshop

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

Or Litany, Daniel Freedman

Comments ICLR workshop on Learning from Limited Labeled Data (LLD) -- Best Paper Award

Learning Embeddings into Entropic Wasserstein Spaces

Charlie Frogner, Farzaneh Mirzazadeh, Justin Solomon

Comments ICLR 2019

Function Space Particle Optimization for Bayesian Neural Networks

Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang

Comments Extended version of the ICLR'19 paper

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville

Comments Published as a conference paper at ICLR 2019

Automatically Composing Representation Transformations as a Means for Generalization

Michael B. Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths

Comments Accepted to the International Conference on Learning Representations 2019