ICLR

DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images

Taihong Xiao, Jiapeng Hong, Jinwen Ma

Comments ICLR 2018 workshop, github: https://github.com/Prinsphield/DNA-GAN

Fraternal Dropout

Konrad Zolna, Devansh Arpit, Dendi Suhubdy, Yoshua Bengio

Comments Accepted to ICLR 2018. Extended appendix. Added official GitHub code for replication: https://github.com/kondiz/fraternal-dropout . Added references. Corrected typos

A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training

Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao

Comments The 6th International Conference on Learning Representations (ICLR 2018), Workshop Track

Global optimality conditions for deep neural networks

Chulhee Yun, Suvrit Sra, Ali Jadbabaie

Comments 14 pages. A camera-ready version that will appear at ICLR 2018

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Daniel Fojo, Víctor Campos, Xavier Giro-i-Nieto

Comments Accepted as workshop paper at ICLR 2018

A Dataset To Evaluate The Representations Learned By Video Prediction Models

Ryan Szeto, Simon Stent, German Ros, Jason J. Corso

Comments Accepted to ICLR 2018 Workshop Track. Fixed Figure 2

Uncertainty Estimation via Stochastic Batch Normalization

Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry Vetrov

Comments Under review as a workshop paper at ICLR 2018

Journal ref Workshop track - ICLR 2018

Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines

Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M Bayen, Sham Kakade, Igor Mordatch, Pieter Abbeel

Comments Accepted to ICLR 2018, Oral (2%)

Fix your classifier: the marginal value of training the last weight layer

Elad Hoffer, Itay Hubara, Daniel Soudry

Comments https://openreview.net/forum?id=S1Dh8Tg0-

Journal ref International Conference on Learning Representations 2018

A DIRT-T Approach to Unsupervised Domain Adaptation

Rui Shu, Hung H. Bui, Hirokazu Narui, Stefano Ermon

Comments ICLR 2018

Learning to cluster in order to transfer across domains and tasks

Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira

Comments ICLR 2018

Cascade Adversarial Machine Learning Regularized with a Unified Embedding

Taesik Na, Jong Hwan Ko, Saibal Mukhopadhyay

Comments 16 pages, 9 figures, International Conference on Learning Representations (ICLR) 2018

Towards Image Understanding from Deep Compression without Decoding

Robert Torfason, Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool

Comments ICLR 2018 conference paper

Emergent Complexity via Multi-Agent Competition

Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch

Comments Published as a conference paper at ICLR 2018

Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks

Youngjin Kim, Minjung Kim, Gunhee Kim

Comments Published in ICLR 2018

Non-Autoregressive Neural Machine Translation

Jiatao Gu, James Bradbury, Caiming Xiong, Victor O. K. Li, Richard Socher

Comments Accepted by ICLR 2018

An efficient framework for learning sentence representations

Lajanugen Logeswaran, Honglak Lee

Comments ICLR 2018

Residual Connections Encourage Iterative Inference

Stanisław Jastrzębski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio

Comments First two authors contributed equally. Published in ICLR 2018

Towards Synthesizing Complex Programs from Input-Output Examples

Xinyun Chen, Chang Liu, Dawn Song

Comments Published as a conference paper at ICLR 2018

Learning to SMILE(S)

Stanisław Jastrzębski, Damian Leśniak, Wojciech Marian Czarnecki

Comments Accepted as a workshop contribution to ICLR 2016

Towards better understanding of gradient-based attribution methods for Deep Neural Networks

Marco Ancona, Enea Ceolini, Cengiz Öztireli, Markus Gross

Comments ICLR 2018

Dynamic Coattention Networks For Question Answering

Caiming Xiong, Victor Zhong, Richard Socher

Comments 14 pages, 7 figures, International Conference on Learning Representations 2017

Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect

Xiang Wei, Boqing Gong, Zixia Liu, Wei Lu, Liqiang Wang

Comments Accepted as a conference paper in International Conference on Learning Representation(ICLR). Xiang Wei and Boqing Gong contributed equally in this work

Stochastic Activation Pruning for Robust Adversarial Defense

Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Anima Anandkumar

Comments ICLR 2018

Generalizing Hamiltonian Monte Carlo with Neural Networks

Daniel Levy, Matthew D. Hoffman, Jascha Sohl-Dickstein

Comments ICLR 2018

Breaking the Softmax Bottleneck: A High-Rank RNN Language Model

Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen

Comments ICLR Oral 2018

Deep Neural Networks as Gaussian Processes

Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington, Jascha Sohl-Dickstein

Comments Published version in ICLR 2018. 10 pages + appendix

SEARNN: Training RNNs with Global-Local Losses

Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin, Simon Lacoste-Julien

Comments Published as a conference paper at ICLR 2018, 16 pages

Skip Connections Eliminate Singularities

A. Emin Orhan, Xaq Pitkow

Comments Published as a conference paper at ICLR 2018

Distributed Prioritized Experience Replay

Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver

Comments Accepted to International Conference on Learning Representations 2018