2.1k citations · 4.6k across the 69 of their papers we have counts for
82 papers
Level set methods for gradient-free optimization of metasurface arrays
Alex Saad-Falcon, Christopher Howard, Justin Romberg +1
Global optimization techniques are increasingly preferred over human-driven methods in the design of electromagnetic structures such as metasurfaces, and careful construction and p…
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
Jihui Jin, Etienne Ollivier, Richard Touret +3
Inverse problems describe the task of recovering an underlying signal of interest given observables. Typically, the observables are related via some non-linear forward model applie…
Decentralized and Privacy-Preserving Learning of Approximate Stackelberg Solutions in Energy Trading Games with Demand Response Aggregators
Styliani I. Kampezidou, Justin Romberg, Kyriakos G. Vamvoudakis +1
In this work, a novel Stackelberg game theoretic framework is proposed for trading energy bidirectionally between the demand-response (DR) aggregator and the prosumers. This formul…
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
Sihan Zeng, Thinh T. Doan, Justin Romberg
The aim of this paper is to improve the understanding of the optimization landscape for policy optimization problems in reinforcement learning. Specifically, we show that the super…
Iterative Broadband Source Localization
Coleman DeLude, Rakshith Sharma, Santhosh Karnik +3
In this paper we consider the problem of localizing a set of broadband sources from a finite window of measurements. In the case of narrowband sources this can be reduced to the pr…
Loop Unrolled Shallow Equilibrium Regularizer (LUSER) -- A Memory-Efficient Inverse Problem Solver
Peimeng Guan, Jihui Jin, Justin Romberg +1
In inverse problems we aim to reconstruct some underlying signal of interest from potentially corrupted and often ill-posed measurements. Classical optimization-based techniques pr…