Papers
A New Distribution on the Simplex with Auto-Encoding Applications
Andrew Stirn, Tony Jebara, David Knowles
On the Correctness and Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
Yulia Rubanova, Ricky T. Q. Chen, David K. Duvenaud
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response
Fan Zhou, Tengfei Li, Haibo Zhou et al.
Provably robust boosted decision stumps and trees against adversarial attacks
Maksym Andriushchenko, Matthias Hein
Facility Location Problem in Differential Privacy Model Revisited
Yunus Esencayi, Marco Gaboardi, Shi Li et al.
PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson et al.
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
Satoshi Tsutsui, Yanwei Fu, David Crandall
Differentially Private Covariance Estimation
Kareem Amin, Travis Dick, Alex Kulesza et al.
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
Shashank Rajput, Hongyi Wang, Zachary Charles et al.
Bootstrapping Upper Confidence Bound
Botao Hao, Yasin Abbasi Yadkori, Zheng Wen et al.
Information-Theoretic Confidence Bounds for Reinforcement Learning
Xiuyuan Lu, Benjamin Van Roy
Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach
Shuyue Hu, Chin-wing Leung, Ho-fung Leung
Faster Boosting with Smaller Memory
Julaiti Alafate, Yoav S Freund
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
Vikas Garg, Tamar Pichkhadze
First-order methods almost always avoid saddle points: The case of vanishing step-sizes
Ioannis Panageas, Georgios Piliouras, Xiao Wang
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
Yu Qi, Bin Liu, Yueming Wang et al.
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning
Wenhao Yang, Xiang Li, Zhihua Zhang
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Mark Bun, Thomas Steinke
Learning Robust Global Representations by Penalizing Local Predictive Power
Haohan Wang, Songwei Ge, Zachary Lipton et al.
A Self Validation Network for Object-Level Human Attention Estimation
Zehua Zhang, Chen Yu, David Crandall
Robust and Communication-Efficient Collaborative Learning
Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari et al.
Defending Against Neural Fake News
Rowan Zellers, Ari Holtzman, Hannah Rashkin et al.
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
Arun Verma, Manjesh Hanawal, Arun Rajkumar et al.
Learning Positive Functions with Pseudo Mirror Descent
Yingxiang Yang, Haoxiang Wang, Negar Kiyavash et al.