ICLR

Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

Comments Accepted to ICLR 2020

DiffTaichi: Differentiable Programming for Physical Simulation

Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Frédo Durand

Comments Published at ICLR 2020

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack

Minhao Cheng, Simranjit Singh, Patrick Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh

Comments Published in ICLR 2020

Abductive Commonsense Reasoning

Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, Yejin Choi

Comments ICLR 2020 Camera Ready

Four Things Everyone Should Know to Improve Batch Normalization

Cecilia Summers, Michael J. Dinneen

Comments ICLR 2020, 18 pages

Deep Semi-Supervised Anomaly Detection

Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft

Comments 23 pages, Published as a conference paper at ICLR 2020

Disentangling Factors of Variation Using Few Labels

Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem

Journal ref Eighth International Conference on Learning Representations - ICLR 2020

Progressive Memory Banks for Incremental Domain Adaptation

Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang

Comments ICLR 2020

Automatically Discovering and Learning New Visual Categories with Ranking Statistics

Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman

Comments ICLR 2020, code: http://www.robots.ox.ac.uk/~vgg/research/auto_novel

Intrinsic Motivation for Encouraging Synergistic Behavior

Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, Abhinav Gupta

Comments ICLR 2020 camera-ready

Multilingual Alignment of Contextual Word Representations

Steven Cao, Nikita Kitaev, Dan Klein

Comments ICLR 2020

Probability Calibration for Knowledge Graph Embedding Models

Pedro Tabacof, Luca Costabello

Comments ICLR 2020

Measuring the Reliability of Reinforcement Learning Algorithms

Stephanie C. Y. Chan, Samuel Fishman, John Canny, Anoop Korattikara, Sergio Guadarrama

Comments Accepted for publication at ICLR 2020 (spotlight)

Mixed-curvature Variational Autoencoders

Ondrej Skopek, Octavian-Eugen Ganea, Gary Bécigneul

Comments ICLR 2020 camera ready version

Journal ref International Conference on Learning Representations (ICLR) 2020

Single Episode Policy Transfer in Reinforcement Learning

Jiachen Yang, Brenden Petersen, Hongyuan Zha, Daniel Faissol

Comments Published at International Conference on Learning Representations 2020

At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?

Niv Giladi, Mor Shpigel Nacson, Elad Hoffer, Daniel Soudry

Comments ICLR 2020 Camera ready version

PairNorm: Tackling Oversmoothing in GNNs

Lingxiao Zhao, Leman Akoglu

Comments ICLR 2020 Camera Ready

Self-Adversarial Learning with Comparative Discrimination for Text Generation

Wangchunshu Zhou, Tao Ge, Ke Xu, Furu Wei, Ming Zhou

Comments ICLR 2020

Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation

Hang Gao, Xizhou Zhu, Steve Lin, Jifeng Dai

Comments Project page: http://people.eecs.berkeley.edu/~hangg/deformable-kernels/. Accepted as conference paper in ICLR 2020. First two authors contributed equally

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals

Comments ICLR 2020

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation

Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

Comments ICLR 2020 Camera-Ready. Previous title: VideoFlow: A Flow-Based Generative Model for Video

Smoothness and Stability in GANs

Casey Chu, Kentaro Minami, Kenji Fukumizu

Comments ICLR 2020

Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar

Journal ref In Proc. 8th International Conference on Learning Representations (ICLR 2020)

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski

Comments New version that includes changes made during the ICLR 2020 review process (https://openreview.net/forum?id=rkgvXlrKwH)

Scaling Autoregressive Video Models

Dirk Weissenborn, Oscar Täckström, Jakob Uszkoreit

Comments International Conference on Learning Representations (ICLR) 2020

Geometric Insights into the Convergence of Nonlinear TD Learning

David Brandfonbrener, Joan Bruna

Comments ICLR 2020

Graph Convolutional Reinforcement Learning

Jiechuan Jiang, Chen Dun, Tiejun Huang, Zongqing Lu

Comments ICLR'20

Pre-training Tasks for Embedding-based Large-scale Retrieval

Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar

Comments Accepted by ICLR 2020

Iterative energy-based projection on a normal data manifold for anomaly localization

David Dehaene, Oriel Frigo, Sébastien Combrexelle, Pierre Eline

Comments ICLR 2020

Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data

David W. Romero, Mark Hoogendoorn

Comments Proceedings of the 8th International Conference on Learning Representations (ICLR), 2020

Journal ref Proceedings of the International Conference on Learning Representations, 2020