activity
20192022
most citedStabilizing Dynamical Systems via Policy Gradient Methods

13 citations · 24 across the 3 of their papers we have counts for

collaborators

7 papers

math.OC20225 cited

Globally Convergent Policy Search over Dynamic Filters for Output Estimation

Jack Umenberger, Max Simchowitz, Juan C. Perdomo +2

We introduce the first direct policy search algorithm which provably converges to the globally optimal filter for the classical problem of predicting the outputs…

eess.SY202113 cited

Stabilizing Dynamical Systems via Policy Gradient Methods

Juan C. Perdomo, Jack Umenberger, Max Simchowitz

Stabilizing an unknown control system is one of the most fundamental problems in control systems engineering. In this paper, we provide a simple, model-free algorithm for stabilizi…

math.OC2021

Towards a Dimension-Free Understanding of Adaptive Linear Control

Juan C. Perdomo, Max Simchowitz, Alekh Agarwal +1

We study the problem of adaptive control of the linear quadratic regulator for systems in very high, or even infinite dimension. We demonstrate that while sublinear regret requires…

cs.LG2021

Outside the Echo Chamber: Optimizing the Performative Risk

John Miller, Juan C. Perdomo, Tijana Zrnic

In performative prediction, predictions guide decision-making and hence can influence the distribution of future data. To date, work on performative prediction has focused on findi…

cs.LG2020

Stochastic Optimization for Performative Prediction

Celestine Mendler-Dünner, Juan C. Perdomo, Tijana Zrnic +1

In performative prediction, the choice of a model influences the distribution of future data, typically through actions taken based on the model's predictions. We initiate the stud…

cs.LG2020

Performative Prediction

Juan C. Perdomo, Tijana Zrnic, Celestine Mendler-Dünner +1

When predictions support decisions they may influence the outcome they aim to predict. We call such predictions performative; the prediction influences the target. Performativity i…