9 papers
Rate-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator
Spencer Hutchinson, Nanfei Jiang, Mahnoosh Alizadeh
We study the problem of adaptive control of the stochastic linear quadratic regulator (LQR) with constraints that must be satisfied at every time step. Prior work on the multidimen…
Pricing Electric Vehicle Charging and Station Access via Copositive Duality
Nanfei Jiang, Yi Zhou, Josh A. Taylor +1
Optimized charging of electric vehicles (EVs) at public locations consists of two decisions: how much energy to deliver at what times, which is continuous, and where to plug in, wh…
Stochastic Gradient Descent with Strategic Querying
Nanfei Jiang, Hoi-To Wai, Mahnoosh Alizadeh
This paper considers a finite-sum optimization problem under first-order queries and investigates the benefits of strategic querying on stochastic gradient-based methods compared t…
The Safety-Privacy Tradeoff in Linear Bandits
Arghavan Zibaie, Spencer Hutchinson, Ramtin Pedarsani +1
We consider a collection of linear stochastic bandit problems, each modeling the random response of different agents to proposed interventions, coupled together by a global safety…
Constrained Online Convex Optimization with Polyak Feasibility Steps
Spencer Hutchinson, Mahnoosh Alizadeh
In this work, we study online convex optimization with a fixed constraint function . Prior work on this problem has shown reg…
Online Nonstochastic Control with Convex Safety Constraints
Nanfei Jiang, Spencer Hutchinson, Mahnoosh Alizadeh
This paper considers the online nonstochastic control problem of a linear time-invariant system under convex state and input constraints that need to be satisfied at all times. We…
Learning Prosumer Behavior in Energy Communities: Integrating Bilevel Programming and Online Learning
Bennevis Crowley, Jalal Kazempour, Lesia Mitridati +1
Dynamic pricing through bilevel programming is widely used for demand response but often assumes perfect knowledge of prosumer behavior, which is unrealistic in practical applicati…
Safe Online Convex Optimization with Multi-Point Feedback
Spencer Hutchinson, Mahnoosh Alizadeh
Motivated by the stringent safety requirements that are often present in real-world applications, we study a safe online convex optimization setting where the player needs to simul…
Optimistic Safety for Online Convex Optimization with Unknown Linear Constraints
Spencer Hutchinson, Tianyi Chen, Mahnoosh Alizadeh
We study the problem of online convex optimization (OCO) under unknown linear constraints that are either static, or stochastically time-varying. For this problem, we introduce an…