101 citations · 303 across the 42 of their papers we have counts for
8 papers · 1 filter
Robust Receding Horizon Games with Additive Uncertainty
Dinesh Patra, Tanish Jain, Ashish R. Hota
We study a receding horizon game in which multiple agents drive linear systems subject to additive disturbances, private state and input constraints, and shared coupling constraint…
Optimal protection and vaccination against epidemics with reinfection risk
Urmee Maitra, Ashish R. Hota, Rohit Gupta +1
We consider the problem of the optimal allocation of vaccination and protection measures for the Susceptible-Infected-Recovered-Infected (SIRI) epidemiological model, which general…
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…
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…
Consistency of Distributionally Robust Risk- and Chance-Constrained Optimization under Wasserstein Ambiguity Sets
Ashish Cherukuri, Ashish R. Hota
We study stochastic optimization problems with chance and risk constraints, where in the latter, risk is quantified in terms of the conditional value-at-risk (CVaR). We consider th…
Wasserstein Distributionally Robust Look-Ahead Economic Dispatch
Bala Kameshwar Poolla, Ashish R. Hota, Saverio Bolognani +2
We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy g…