Accepted Papers
Rishav Chourasia, Adish Singla, Unifying Ensemble Methods for Q-learning via Social Choice Theory
Yoshihiro Nagano, Shiro Takagi, Yuki Yoshida, Masato Okada, Localized Generations with Self-Supervised Meta-Learning
Phi Vu Tran, Integrating Self-Supervised Regularization for Supervised and Semi-Supervised Learning
Evan Shelhamer, Dequan Wang, Bruno A Olshausen, Trevor Darrell, Dynamic Scale Inference by Entropy Minimization
Mayoore Jaiswal, Bumsoo Kang, Jinho Lee, Minsik Cho, MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Weitang Liu, John D Owens, Emad Barsoum, Object Localization with a Weakly Supervised CapsNet
Benedikt Boecking, Artur Dubrawski, Pairwise Feedback for Data Programming
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris, Support-guided Adversarial Imitation Learning
Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Knowledge Refinery: Learning from Erroneous Knowledge with Residual Label
Jindong Gu, Zhiliang Wu, Volker Tresp, Learning with Knowledge in Explanations
Ziming Li, Julia Kiseleva, Alekh Agarwal, Maarten de Rijke, Learning Data-Driven Objectives to Optimize Interactive Systems
Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski, Thresholding Bandit Problem with Dueling Choices
Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang, Adaptive Region-Based Active Learning
John D Co-Reyes, Suvansh Q Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine, Ecological Reinforcement Learning
(Anonymous authors), Advancing Seq2seq Models with Joint Paraphrase Learning
Vikram Voleti, David Kanaa, Simple Video Generation using Neural ODEs
Laura M Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine, AVID: Translating Human Demonstrations for Automated Learning
Galen Chuang, Giulia DeSalvo, Laz Karydas, Jean-François Kagy, Afshin Rostamizadeh, A Theeraphol, Active Learning Empirical Study
Seyed Kamyar Seyed Ghasemipour, Richard Zemel, Shixiang Gu, A Divergence Minimization Perspective on Imitation Learning and State-Marginal Matching
Chenghui Zhou, Chun-Liang Li, Barnabas Poczos, Program Synthesis for Images using Tree-Structured LSTM
Jiacheng Zhu, Shenghao Qin, Jimmy Qin, Wenshuo Wang, Ding Zhao, Recurrent Attentive Neural Process for Sequential Data
Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof, Combining reward information from multiple sources
Shouvik Mani, Mehdi Maasoumy, Sina Pakazad, Expert-guided Regularization via Distance Metric Learning
Dinesh Khandelwal, Suyash Agrawal, Parag Singla, Chetan Arora, Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alex J Smola, Meta-Q-Learning
Xiaoyan Li, Yifeng Li, Anomaly Detection Based on Unsupervised Disentangled Representation Learning in Combination with Manifold Learning
Adrien Bardes, Yu-Xiong Wang, Ruslan Salakhutdinov, Martial Hebert, Progressive Knowledge Distillation For Generative Modeling
Miao Xu, Bingcong Li, Gang Niu, Bo Han, Masashi Sugiyama, Revisiting Sample Selection Approach to Positive-Unlabeled Learning