ICLR

Global-to-local Memory Pointer Networks for Task-Oriented Dialogue

Chien-Sheng Wu, Richard Socher, Caiming Xiong

Comments ICLR 2019

Feature Intertwiner for Object Detection

Hongyang Li, Bo Dai, Shaoshuai Shi, Wanli Ouyang, Xiaogang Wang

Comments ICLR 2019

Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors

Andrew Ilyas, Logan Engstrom, Aleksander Madry

Comments To appear at ICLR 2019; Code available at https://git.io/blackbox-bandits

Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness

Jörn-Henrik Jacobsen, Jens Behrmannn, Nicholas Carlini, Florian Tramèr, Nicolas Papernot

Comments Accepted at the ICLR 2019 SafeML Workshop

Residual Non-local Attention Networks for Image Restoration

Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, Yun Fu

Comments To appear in ICLR 2019

Learning concise representations for regression by evolving networks of trees

William La Cava, Tilak Raj Singh, James Taggart, Srinivas Suri, Jason H. Moore

Comments 16 pages, 11 figures (including Appendix), published in ICLR 2019

Value Propagation Networks

Nantas Nardelli, Gabriel Synnaeve, Zeming Lin, Pushmeet Kohli, Philip H. S. Torr, Nicolas Usunier

Comments Updated to match ICLR 2019 OpenReview's version

Multi-Domain Adversarial Learning

Alice Schoenauer-Sebag, Louise Heinrich, Marc Schoenauer, Michele Sebag, Lani F. Wu, Steve J. Altschuler

Comments Accepted at ICLR'19

Journal ref ICLR 2019-Seventh annual International Conference on Learning Representations

Complement Objective Training

Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan

Comments ICLR'19 Camera Ready

Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs

Sachin Kumar, Yulia Tsvetkov

Comments Seventh International Conference on Learning Representations (ICLR 2019)

Transferring Knowledge across Learning Processes

Sebastian Flennerhag, Pablo G. Moreno, Neil D. Lawrence, Andreas Damianou

Comments Published as a conference paper at ICLR 2019; 23 pages, 8 figures, 6 tables

Unsupervised Learning via Meta-Learning

Kyle Hsu, Sergey Levine, Chelsea Finn

Comments ICLR 2019 camera-ready. 24 pages, 2 figures, links to code available at https://sites.google.com/view/unsupervised-via-meta

Learning to Remember More with Less Memorization

Hung Le, Truyen Tran, Svetha Venkatesh

Comments Accepted to ICLR'19, oral presentation

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

Comments To appear at ICLR 2019

Learning Robust Representations by Projecting Superficial Statistics Out

Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing

Comments To appear at ICLR 2019. Implementation: https://github.com/HaohanWang/HEX

Improving the Generalization of Adversarial Training with Domain Adaptation

Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft

Comments ICLR 2019

Functional Variational Bayesian Neural Networks

Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger Grosse

Comments ICLR 2019

Learning Implicitly Recurrent CNNs Through Parameter Sharing

Pedro Savarese, Michael Maire

Comments Published as a conference paper at ICLR 2019

Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency

Liqian Ma, Xu Jia, Stamatios Georgoulis, Tinne Tuytelaars, Luc Van Gool

Comments To appear in ICLR 2019

DeepOBS: A Deep Learning Optimizer Benchmark Suite

Frank Schneider, Lukas Balles, Philipp Hennig

Comments Accepted at ICLR 2019. 9 pages, 3 figures, 2 tables

Unsupervised Discovery of Parts, Structure, and Dynamics

Zhenjia Xu, Zhijian Liu, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

Comments ICLR 2019. The first two authors contributed equally to this work

Robust Conditional Generative Adversarial Networks

Grigorios G. Chrysos, Jean Kossaifi, Stefanos Zafeiriou

Comments To appear in ICLR 2019

Fixup Initialization: Residual Learning Without Normalization

Hongyi Zhang, Yann N. Dauphin, Tengyu Ma

Comments Updating reference. Accepted for publication at ICLR 2019; see https://openreview.net/forum?id=H1gsz30cKX

Trellis Networks for Sequence Modeling

Shaojie Bai, J. Zico Kolter, Vladlen Koltun

Comments Published at ICLR 2019

Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information

Arjun Sharma, Mohit Sharma, Nicholas Rhinehart, Kris M. Kitani

Comments Accepted as conference paper at ICLR'19

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks

Reinhard Heckel, Paul Hand

Comments International Conference on Learning Representations 2019

Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks

Jose Oramas, Kaili Wang, Tinne Tuytelaars

Comments Accepted at International Conference on Learning Representations (ICLR) 2019. Project website: http://homes.esat.kuleuven.be/~joramas/projects/visualExplanationByInterpretation

Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions

Matthew MacKay, Paul Vicol, Jon Lorraine, David Duvenaud, Roger Grosse

Comments Published as a conference paper at ICLR 2019

Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization

Takayuki Osa, Voot Tangkaratt, Masashi Sugiyama

Comments 16 pages, ICLR 2019

M$^3$RL: Mind-aware Multi-agent Management Reinforcement Learning

Tianmin Shu, Yuandong Tian

Comments ICLR 2019; 18 pages, 12 figures