XVII th Conference on Stochastic Programming

Expanding the reach of progressive hedging methods

1 août 2025, 11:15

30m

F107

Contributed talk Stochastic Programming Stochastic Programming

Orateur

Dr Claudia Sagastizábal (IMECC)

Description

Many popular splitting methods for large-scale stochastic optimization are derived from Spingarn's partial inverse framework. Well-known and popular methods such as Progressive Hedging and Proximal Decomposition are paradigmatic examples of this class. We present lessons learned by examining Spingarn's framework from a dual perspective, inspired from bundle methods in nonsmooth optimization.

Joint work with Felipe Atenas, Theo Molfessis and Mikhail Solodov