5 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems
Dimitris Boskos, Jorge Cortés, Sonia Martínez
This paper builds Wasserstein ambiguity sets for the unknown probability distribution of dynamic random variables leveraging noisy partial-state observations. The constructed ambig…
Resource-Aware Discretization of Accelerated Optimization Flows
Miguel Vaquero, Pol Mestres, Jorge Cortés
This paper tackles the problem of discretizing accelerated optimization flows while retaining their convergence properties. Inspired by the success of resource-aware control in dev…
Data-driven ambiguity sets with probabilistic guarantees for dynamic processes
Dimitris Boskos, Jorge Cortés, Sonia Martínez
Distributional ambiguity sets provide quantifiable ways to characterize the uncertainty about the true probability distribution of random variables of interest. This makes them a k…
Frequency-driven market mechanisms for optimal dispatch in power networks
Tjerk Stegink, Ashish Cherukuri, Claudio De Persis +2
This paper studies real-time bidding mechanisms for economic dispatch and frequency regulation in electrical power networks. We consider a market administered by an independent sys…