Seminar Details
2024-11-19 (14h) : Large-scale Stochastic Optimization: Approximations and Distributed Methods
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Ashish Cherukuri (University of Groningen)
Abstract :
This talk focuses on stochastic optimization problems defined over a network and explores data-driven distributionally robust (DR) solution methods to solve it. Specifically, we will look at chance-constrained optimization that finds application in generation planning problem and expectation minimization problem that is motivated by distributed optimization and federated learning. The DR formulations of the problem have attractive statistical guarantees but pose computational difficulties. The talk will provide algorithms to handle these challenges, paying special attention to the large-scale nature of the problem and the fact that the data about the uncertainty cannot be aggregated at one single location in the network. We will end the talk with future challenges and research directions.