This tutorial serves as an introduction to recently developed non-asympt...
For a receding-horizon controller with a known system and with an approx...
The setting of an agent making decisions under uncertainty and under dyn...
This tutorial survey provides an overview of recent non-asymptotic advan...
We study stochastic policy gradient methods from the perspective of
cont...
In this paper, we study the statistical difficulty of learning to contro...
In this paper, we address the stochastic MPC (SMPC) problem for linear
s...
The least squares problem with L1-regularized regressors, called Lasso, ...
In this paper, we investigate when system identification is statisticall...
In this work, we study the problem of finding approximate, with minimum
...
We provide an efficient and private solution to the problem of
encryptio...
In this paper, we consider the problem of predicting observations genera...
In this paper, we consider the task of designing a Kalman Filter (KF) fo...
In this paper, we analyze the finite sample complexity of stochastic sys...