Showing math.OCShow all
2 papers · 1 filter
math.OC2022
Data-driven distributionally robust optimization over a network via distributed semi-infinite programming
Ashish Cherukuri, Alireza Zolanvari, Goran Banjac +1
This paper focuses on solving a data-driven distributionally robust optimization problem over a network of agents. The agents aim to minimize the worst-case expected cost computed…
math.OC2021
Breaking the Convergence Barrier: Optimization via Fixed-Time Convergent Flows
Param Budhraja, Mayank Baranwal, Kunal Garg +1
Accelerated gradient methods are the cornerstones of large-scale, data-driven optimization problems that arise naturally in machine learning and other fields concerning data analys…