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Program for stream Statistical learning, stochastic optimization and applications
Monday
Tuesday
Wednesday
Thursday
Thursday, 10:00-11:40
HB-09: Optimization and Multi-agent Reinforcement Learning
Stream: Statistical learning, stochastic optimization and applications
Room: Room 9
Chair(s):
Xiangfeng Wang, Tsung-Hui Chang
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A Proximal Dual Consensus Method for Linearly Coupled Multi-Agent Non-Convex Optimization
Tsung-Hui Chang -
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Xiangfeng Wang -
A Peaceman-Rachford splitting method with monotone plus skew-symmetric splitting for nonlinear saddle point problems
Wenxing Zhang
Friday
Friday, 10:00-11:40
FB-09: Sequential learning in operations research
Stream: Statistical learning, stochastic optimization and applications
Room: Room 9
Chair(s):
Dongwook Shin, Nandini Seth
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Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi -
Thompson Sampling with Information Relaxation Penalties
Seungki Min, Ciamac Moallemi, Costis Maglaras -
A Two- Stage Mechanism for Online Grocery Recommendation using Bayesian Bandits
Nandini Seth, Dinesh Kumar
Friday, 12:00-13:40
FC-06: Simulation, statistical learning and applications
Stream: Statistical learning, stochastic optimization and applications
Room: Room 6
Chair(s):
Xinyun Chen
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On the convergence of an improved and adaptive kinetic simulated annealing
Michael Choi -
Neural Learning of Online Consumer Credit Risk
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Online optimal pricing and capacity sizing for G/G/1 queue with demand learning
Xinyun Chen -
From Hotelling to Nakamomo: The Economic Meaning of Bitcoin Mining
Wei Jiang