Papers
On the Calibration of Multiclass Classification with Rejection
Chenri Ni, Nontawat Charoenphakdee, Junya Honda et al.
Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration
Jianchun Chen, Lingjing Wang, Xiang Li et al.
Learning in Generalized Linear Contextual Bandits with Stochastic Delays
Zhengyuan Zhou, Renyuan Xu, Jose Blanchet
Competitive Gradient Descent
Florian Schaefer, Anima Anandkumar
Non-Cooperative Inverse Reinforcement Learning
Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling et al.
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data
Qian Lou, Lei Jiang
Demystifying Black-box Models with Symbolic Metamodels
Ahmed M. Alaa, Mihaela van der Schaar
Mutually Regressive Point Processes
Ifigeneia Apostolopoulou, Scott Linderman, Kyle Miller et al.
Deep Structured Prediction for Facial Landmark Detection
Lisha Chen, Hui Su, Qiang Ji
Disentangling Influence: Using disentangled representations to audit model predictions
Charles Marx, Richard Phillips, Sorelle Friedler et al.
Streaming Bayesian Inference for Crowdsourced Classification
Edoardo Manino, Long Tran-Thanh, Nicholas Jennings
Discriminative Topic Modeling with Logistic LDA
Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak et al.
Real-Time Reinforcement Learning
Simon Ramstedt, Chris Pal
On the Power and Limitations of Random Features for Understanding Neural Networks
Gilad Yehudai, Ohad Shamir
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games
Kaiqing Zhang, Zhuoran Yang, Tamer Basar
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi et al.
Bayesian Learning of Sum-Product Networks
Martin Trapp, Robert Peharz, Hong Ge et al.
Total Least Squares Regression in Input Sparsity Time
Huaian Diao, Zhao Song, David Woodruff et al.
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels
Natalia Neverova, David Novotny, Andrea Vedaldi
Unsupervised Scalable Representation Learning for Multivariate Time Series
Jean-Yves Franceschi, Aymeric Dieuleveut, Martin Jaggi
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Robert Kleinberg, Kevin Leyton-Brown, Brendan Lucier et al.
Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes
Gunpil Hwang, Seohyeon Kim, Hyeon-Min Bae
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs
Himanshu Sahni, Toby Buckley, Pieter Abbeel et al.
Learning Reward Machines for Partially Observable Reinforcement Learning
Rodrigo Toro Icarte, Ethan Waldie, Toryn Klassen et al.
Learning Sample-Specific Models with Low-Rank Personalized Regression
Ben Lengerich, Bryon Aragam, Eric P Xing