ICLR

ES-MAML: Simple Hessian-Free Meta Learning

Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang

Comments Published as a conference paper in ICLR 2020. Code can be found in http://github.com/google-research/google-research/tree/master/es_maml

Harnessing Structures for Value-Based Planning and Reinforcement Learning

Yuzhe Yang, Guo Zhang, Zhi Xu, Dina Katabi

Comments ICLR 2020 (Oral)

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness

Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin

Comments accepted by ICLR 2020

HydroNets: Leveraging River Structure for Hydrologic Modeling

Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv

Comments Presented in the "AI for physical sciences" workshop, ICLR2020 (https://ai4earthscience.github.io/iclr-2020-workshop/)

Exploring Exploration: Comparing Children with RL Agents in Unified Environments

Eliza Kosoy, Jasmine Collins, David M. Chan, Sandy Huang, Deepak Pathak, Pulkit Agrawal, John Canny, Alison Gopnik, Jessica B. Hamrick

Comments Published as a workshop paper at "Bridging AI and Cognitive Science" (ICLR 2020)

Stochastic AUC Maximization with Deep Neural Networks

Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang

Comments Accepted by ICLR 2020

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints

Mengtian Li, Ersin Yumer, Deva Ramanan

Comments ICLR 2020. Project page with code is at http://www.cs.cmu.edu/~mengtial/proj/budgetnn/

Encoding word order in complex embeddings

Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen

Comments 15 pages, 3 figures, ICLR 2020 spotlight paper. A typo on Ablation Table was revised thanks to Jingquan Zeng from SCUT

AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud Processing

Xingzhe He, Helen Lu Cao, Bo Zhu

Comments ICLR 2020

Measuring Compositional Generalization: A Comprehensive Method on Realistic Data

Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet

Comments Accepted for publication at ICLR 2020

Convolutional Conditional Neural Processes

Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner

Comments Accepted at International Conference on Learning Representations 2020

On the Convergence of FedAvg on Non-IID Data

Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang

Comments 2020 International Conference on Learning Representations

Surrogate sea ice model enables efficient tuning

Kelly Kochanski, Ivana Cvijanovic, Donald Lucas

Comments 6 pages

Journal ref Presented at the AI for Earth Sciences workshop at the International Conference on Learning Representations, 2020

On the interaction between supervision and self-play in emergent communication

Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

Comments The first two authors contributed equally. Accepted at ICLR 2020

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Yujun Lin, Song Han, Huizi Mao, Yu Wang, William J. Dally

Comments we find 99.9% of the gradient exchange in distributed SGD is redundant; we reduce the communication bandwidth by two orders of magnitude without losing accuracy. Code is available at: https://github.com/synxlin/deep-gradient-compression

Journal ref ICLR 2018

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection

Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu

Comments Published in ICLR 2020

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning

Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin Riedmiller

Journal ref ICLR 2020

Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation

Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou

Comments ICLR 2020 (updated to fix a typo in Algorithm 1)

Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue

Byeongchang Kim, Jaewoo Ahn, Gunhee Kim

Comments Published in ICLR 2020 (Spotlight)

Continual Learning with Adaptive Weights (CLAW)

Tameem Adel, Han Zhao, Richard E. Turner

Comments ICLR 2020

Hypermodels for Exploration

Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy

Comments Published as a conference paper at ICLR 2020

Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models

Xisen Jin, Zhongyu Wei, Junyi Du, Xiangyang Xue, Xiang Ren

Comments ICLR 2020

TabFact: A Large-scale Dataset for Table-based Fact Verification

Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, William Yang Wang

Comments Accepted to ICLR 2020, 17 pages, 15 figures. Main paper has 9 pages

Dynamic Model Pruning with Feedback

Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

Comments appearing at ICLR 2020

Multi-Agent Interactions Modeling with Correlated Policies

Minghuan Liu, Ming Zhou, Weinan Zhang, Yuzheng Zhuang, Jun Wang, Wulong Liu, Yong Yu

Comments 20 pages (10 pages of supplementary), 5 figures, Accepted by The Eighth International Conference on Learning Representations (ICLR 2020)

Anytime MiniBatch: Exploiting Stragglers in Online Distributed Optimization

Nuwan Ferdinand, Haider Al-Lawati, Stark C. Draper, Matthew Nokleby

Comments International Conference on Learning Representations (ICLR), May 2019, New Orleans, LA, USA

Journal ref Proc. of the 7th Int. Conf. on Learning Representations (ICLR), May 2019, New Orleans, LA, USA

Memory-Based Graph Networks

Amir Hosein Khasahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris

Comments ICLR 2020

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification

Ting Chen, Song Bian, Yizhou Sun

Comments A shorter version titled "Graph Feature Networks" was accepted to ICLR'19 RLGM workshop. code available at https://github.com/chentingpc/gfn

RNA Secondary Structure Prediction By Learning Unrolled Algorithms

Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song

Comments International Conference on Learning Representations 2020

Journal ref International Conference on Learning Representations 2020, https://openreview.net/forum?id=S1eALyrYDH

Causal Discovery with Reinforcement Learning

Shengyu Zhu, Ignavier Ng, Zhitang Chen

Comments ICLR 2020 (oral). This version: minor edits in the appendix. Codes, datasets, and training logs have been made available at https://github.com/huawei-noah/trustworthyAI/tree/master/Causal_Structure_Learning/Causal_Discovery_RL