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Poster
Tue 7:00 On the Noisy Gradient Descent that Generalizes as SGD
Jingfeng Wu · Wenqing Hu · Haoyi Xiong · Jun Huan · Vladimir Braverman · Zhanxing Zhu
Poster
Tue 7:00 Provably Efficient Exploration in Policy Optimization
Qi Cai · Zhuoran Yang · Chi Jin · Zhaoran Wang
Poster
Tue 7:00 Customizing ML Predictions for Online Algorithms
Keerti Anand · Rong Ge · Debmalya Panigrahi
Poster
Tue 7:00 Data Amplification: Instance-Optimal Property Estimation
Yi Hao · Alon Orlitsky
Poster
Tue 7:00 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi · Natalie Frank · Mehryar Mohri
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong · Bo Zeng
Poster
Tue 7:00 From Importance Sampling to Doubly Robust Policy Gradient
Jiawei Huang · Nan Jiang
Poster
Tue 7:00 Asynchronous Coagent Networks
James Kostas · Chris Nota · Philip Thomas
Poster
Tue 7:00 A Free-Energy Principle for Representation Learning
Yansong Gao · Pratik Chaudhari
Poster
Tue 7:00 Maximum-and-Concatenation Networks
Xingyu Xie · Hao Kong · Jianlong Wu · Wayne Zhang · Guangcan Liu · Zhouchen Lin
Poster
Tue 7:00 Familywise Error Rate Control by Interactive Unmasking
Boyan Duan · Aaditya Ramdas · Larry Wasserman
Poster
Tue 7:00 Tensor denoising and completion based on ordinal observations
Chanwoo Lee · Miaoyan Wang