124 citations · 1.6k across the 112 of their papers we have counts for
11 papers · 1 filter
Generating Adversarial Disturbances for Controller Verification
Udaya Ghai, David Snyder, Anirudha Majumdar +1
We consider the problem of generating maximally adversarial disturbances for a given controller assuming only blackbox access to it. We propose an online learning approach to this…
Geometric Exploration for Online Control
Orestis Plevrakis, Elad Hazan
We study the control of an \emph{unknown} linear dynamical system under general convex costs. The objective is minimizing regret vs. the class of disturbance-feedback-controllers,…
Non-Stochastic Control with Bandit Feedback
Paula Gradu, John Hallman, Elad Hazan
We study the problem of controlling a linear dynamical system with adversarial perturbations where the only feedback available to the controller is the scalar loss, and the loss fu…
Online Boosting with Bandit Feedback
Nataly Brukhim, Elad Hazan
We consider the problem of online boosting for regression tasks, when only limited information is available to the learner. We give an efficient regret minimization method that has…
Black-Box Control for Linear Dynamical Systems
Xinyi Chen, Elad Hazan
We consider the problem of controlling an unknown linear time-invariant dynamical system from a single chain of black-box interactions, with no access to resets or offline simulati…
Adaptive Regret for Control of Time-Varying Dynamics
Paula Gradu, Elad Hazan, Edgar Minasyan
We consider the problem of online control of systems with time-varying linear dynamics. This is a general formulation that is motivated by the use of local linearization in control…