Stochastic First-Order Methods in Data Analysis and Reinforcement Learning

Stochastic First-Order Methods in Data Analysis and Reinforcement Learning

Neyman Seminar
Sep 6, 2017, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Mengdi Wang, Princeton University
Stochastic first-order methods provide a basic algorithmic tool for online learning and data analysis. In this talk, we survey several innovative applications including risk-averse optimization, online principal component analysis, dynamic network partition, Markov decision problems and reinforcement learning. We will show that convergence analysis of the stochastic optimization algorithms...