410 citations · 2.1k across the 125 of their papers we have counts for
54 papers · 1 filter
Linear Quadratic Control with Risk Constraints
Anastasios Tsiamis, Dionysios S. Kalogerias, Alejandro Ribeiro +1
We propose a new risk-constrained formulation of the classical Linear Quadratic (LQ) stochastic control problem for general partially-observed systems. Our framework is motivated b…
Encrypted Distributed Lasso for Sparse Data Predictive Control
Andreea B. Alexandru, Anastasios Tsiamis, George J. Pappas
The least squares problem with L1-regularized regressors, called Lasso, is a widely used approach in optimization problems where sparsity of the regressors is desired. This formula…
Learning Lyapunov Functions for Hybrid Systems
Shaoru Chen, Mahyar Fazlyab, Manfred Morari +2
We propose a sampling-based approach to learn Lyapunov functions for a class of discrete-time autonomous hybrid systems that admit a mixed-integer representation. Such systems incl…
Learning Lyapunov Functions for Piecewise Affine Systems with Neural Network Controllers
Shaoru Chen, Mahyar Fazlyab, Manfred Morari +2
We propose a learning-based method for Lyapunov stability analysis of piecewise affine dynamical systems in feedback with piecewise affine neural network controllers. The proposed…
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees
Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado +1
The fragility of deep neural networks to adversarially-chosen inputs has motivated the need to revisit deep learning algorithms. Including adversarial examples during training is a…
Risk-Aware MMSE Estimation
Dionysios S. Kalogerias, Luiz F. O. Chamon, George J. Pappas +1
Despite the simplicity and intuitive interpretation of Minimum Mean Squared Error (MMSE) estimators, their effectiveness in certain scenarios is questionable. Indeed, minimizing sq…