ICLR (Workshop)

Publications

2018

Remi Tachet des Combes, Philip Bachman, Harm van Seijen
Learning Invariances for Policy Generalization. ICLR (Workshop) (2018)
Bowen Baker, Otkrist Gupta, Ramesh Raskar, Nikhil Naik
Accelerating Neural Architecture Search using Performance Prediction. ICLR (Workshop) (2018)
Oliver Hennigh
Automated Design using Neural Networks and Gradient Descent. ICLR (Workshop) (2018)
David Madras, Toniann Pitassi, Richard S. Zemel
Predict Responsibly: Increasing Fairness by Learning to Defer. ICLR (Workshop) (2018)
Soorya Gopalakrishnan, Zhinus Marzi, Upamanyu Madhow, Ramtin Pedarsani
Combating Adversarial Attacks Using Sparse Representations. ICLR (Workshop) (2018)
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry P. Vetrov
Uncertainty Estimation via Stochastic Batch Normalization. ICLR (Workshop) (2018)
Asha Anoosheh, Eirikur Agustsson, Radu Timofte
ComboGAN: Unrestricted Scalability for Image Domain Translation. ICLR (Workshop) (2018)
Yedid Hoshen, Lior Wolf
NAM - Unsupervised Cross-Domain Image Mapping without Cycles or GANs. ICLR (Workshop) (2018)
6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Workshop Track Proceedings ICLR (Workshop) (2018)
Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Ákos Kádár, Adam Trischler, Yoshua Bengio
FigureQA: An Annotated Figure Dataset for Visual Reasoning. ICLR (Workshop) (2018)
Fan Yang, Jiazhong Nie, William W. Cohen, Ni Lao
Learning to Organize Knowledge with N-Gram Machines. ICLR (Workshop) (2018)
Han Zhao, Shanghang Zhang, Guanhang Wu, João Paulo Costeira, José M. F. Moura, Geoffrey J. Gordon
Multiple Source Domain Adaptation with Adversarial Learning. ICLR (Workshop) (2018)
Rinu Boney, Alexander Ilin
Semi-Supervised Few-Shot Learning with MAML. ICLR (Workshop) (2018)
Mateo Rojas-Carulla, Marco Baroni, David Lopez-Paz
Causal Discovery Using Proxy Variables. ICLR (Workshop) (2018)
Yoshihiro Yamada, Masakazu Iwamura, Koichi Kise
ShakeDrop regularization. ICLR (Workshop) (2018)
Roland Fernandez, Asli Celikyilmaz, Paul Smolensky, Rishabh Singh
Learning and Analyzing Vector Encoding of Symbolic Representation. ICLR (Workshop) (2018)
KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
Inference in probabilistic graphical models by Graph Neural Networks. ICLR (Workshop) (2018)
Raghav Goyal, Farzaneh Mahdisoltani, Guillaume Berger, Waseem Gharbieh, Ingo Bax, Roland Memisevic
Evaluating visual "common sense" using fine-grained classification and captioning tasks. ICLR (Workshop) (2018)
Quynh Nguyen, Matthias Hein
The loss surface and expressivity of deep convolutional neural networks. ICLR (Workshop) (2018)
Hiroaki Shioya, Yusuke Iwasawa, Yutaka Matsuo
Extending Robust Adversarial Reinforcement Learning Considering Adaptation and Diversity. ICLR (Workshop) (2018)
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) (2018)
Mika Sarkin Jain, Jack Lindsey
Semiparametric Reinforcement Learning. ICLR (Workshop) (2018)
Yuhui Yuan, Kuiyuan Yang, Jianyuan Guo, Chao Zhang, Jingdong Wang
Feature Incay for Representation Regularization. ICLR (Workshop) (2018)
Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Thomas L. Griffiths
Investigating Human Priors for Playing Video Games. ICLR (Workshop) (2018)
Beidi Chen, Yingchen Xu, Anshumali Shrivastava
Lsh-Sampling breaks the Computational chicken-and-egg Loop in adaptive stochastic Gradient estimation. ICLR (Workshop) (2018)
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
Convolutional Sequence Modeling Revisited. ICLR (Workshop) (2018)
Attila Szabó, Qiyang Hu, Tiziano Portenier, Matthias Zwicker, Paolo Favaro
Challenges in Disentangling Independent Factors of Variation. ICLR (Workshop) (2018)
Ivan Lobov
SpectralWords: Spectral Embeddings Approach to Word Similarity Task for Large Vocabularies. ICLR (Workshop) (2018)
Keyi Yu, Yang Liu, Alexander G. Schwing, Jian Peng
Fast and Accurate Text Classification: Skimming, Rereading and Early Stopping. ICLR (Workshop) (2018)
Risi Kondor, Hy Truong Son, Horace Pan, Brandon M. Anderson, Shubhendu Trivedi
Covariant Compositional Networks For Learning Graphs. ICLR (Workshop) (2018)
Damien Scieur, Edouard Oyallon, Alexandre d'Aspremont, Francis R. Bach
Nonlinear Acceleration of CNNs. ICLR (Workshop) (2018)
Xinyun Chen, Chang Liu, Dawn Song
Tree-to-tree Neural Networks for Program Translation. ICLR (Workshop) (2018)
Zhendong Zhang, Cheolkon Jung
Regularization Neural Networks via Constrained Virtual Movement Field. ICLR (Workshop) (2018)
Yusuke Tsuzuku, Hiroto Imachi, Takuya Akiba
Variance-based Gradient Compression for Efficient Distributed Deep Learning. ICLR (Workshop) (2018)
Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette
Jointly Learning "What" and "How" from Instructions and Goal-States. ICLR (Workshop) (2018)
Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
HoME: a Household Multimodal Environment. ICLR (Workshop) (2018)
Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf
Tempered Adversarial Networks. ICLR (Workshop) (2018)
Yusuke Iwasawa, Kotaro Nakayama, Yutaka Matsuo
Censoring Representations with Multiple-Adversaries over Random Subspaces. ICLR (Workshop) (2018)
Guillaume Alain, Nicolas Le Roux, Pierre-Antoine Manzagol
Negative eigenvalues of the Hessian in deep neural networks. ICLR (Workshop) (2018)
Phiala Shanahan, Daniel Trewartha, William Detmold
Neural network parameter regression for lattice quantum chromodynamics simulations in nuclear and particle physics. ICLR (Workshop) (2018)
Mehran Pesteie, Purang Abolmaesumi, Robert Rohling
Deep Neural Maps. ICLR (Workshop) (2018)
Peter H. Jin, Boris Ginsburg, Kurt Keutzer
Spatially Parallel Convolutions. ICLR (Workshop) (2018)
Zheng Xu, Yen-Chang Hsu, Jiawei Huang
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks. ICLR (Workshop) (2018)
Thomas Elsken, Jan Hendrik Metzen, Frank Hutter
Simple and efficient architecture search for Convolutional Neural Networks. ICLR (Workshop) (2018)
Daniel Neil, Marwin H. S. Segler, Laura Guasch, Mohamed Ahmed, Dean Plumbley, Matthew Sellwood, Nathan Brown
Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design. ICLR (Workshop) (2018)
Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders. ICLR (Workshop) (2018)
Martin Simonovsky, Nikos Komodakis
Towards Variational Generation of Small Graphs. ICLR (Workshop) (2018)
Chenwei Wu, Jiajun Luo, Jason D. Lee
No Spurious Local Minima in a Two Hidden Unit ReLU Network. ICLR (Workshop) (2018)
Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. ICLR (Workshop) (2018)
Charles B. Delahunt, J. Nathan Kutz
A moth brain learns to read MNIST. ICLR (Workshop) (2018)