260 citations · 403 across the 15 of their papers we have counts for
15 papers
Implicit Neural Networks as Static Controllers: Certificates and Performance Separation
Giuseppe C. Calafiore, Laurent El Ghaoui
Implicit neural controllers (INCs) are static feedback laws that are evaluated through an algebraic fixed point {equation}; they include as special cases neural network controllers…
Class-Based Smart Charging Control for Electric Vehicles
Giuseppe C. Calafiore, Luca Ambrosino, Matteo Della Rossa +1
This paper proposes a stochastic control framework for the operation of electric-vehicle (EV) charging stations equipped with on-site photovoltaic (PV) generation and battery stora…
A Distributionally Robust Reinforcement Learning Framework for Constrained Urban EV Dispatch
An Nguyen, Hoang Nguyen, Phuong Le +3
We study city-scale control of electric-vehicle (EV) ride-hailing fleets where dispatch, repositioning, and charging decisions must respect charger and feeder limits under uncertai…
The Extrapolation Power of Implicit Models
Juliette Decugis, Alicia Y. Tsai, Max Emerling +2
In this paper, we investigate the extrapolation capabilities of implicit deep learning models in handling unobserved data, where traditional deep neural networks may falter. Implic…
Sparse Optimization for Unsupervised Extractive Summarization of Long Documents with the Frank-Wolfe Algorithm
Alicia Y. Tsai, Laurent El Ghaoui
We address the problem of unsupervised extractive document summarization, especially for long documents. We model the unsupervised problem as a sparse auto-regression one and appro…
Data-Driven Reachability analysis and Support set Estimation with Christoffel Functions
Alex Devonport, Forest Yang, Laurent El Ghaoui +1
We present algorithms for estimating the forward reachable set of a dynamical system using only a finite collection of independent and identically distributed samples. The produced…
Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems
Fangda Gu, He Yin, Laurent El Ghaoui +3
Neural network controllers have become popular in control tasks thanks to their flexibility and expressivity. Stability is a crucial property for safety-critical dynamical systems,…
Naive Feature Selection: a Nearly Tight Convex Relaxation for Sparse Naive Bayes
Armin Askari, Alexandre d'Aspremont, Laurent El Ghaoui
Due to its linear complexity, naive Bayes classification remains an attractive supervised learning method, especially in very large-scale settings. We propose a sparse version of n…
Robust sketching for multiple square-root LASSO problems
Vu Pham, Laurent El Ghaoui, Arturo Fernandez
Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of le…
Concise comparative summaries (CCS) of large text corpora with a human experiment
Jinzhu Jia, Luke Miratrix, Bin Yu +4
In this paper we propose a general framework for topic-specific summarization of large text corpora and illustrate how it can be used for the analysis of news databases. Our framew…
Sparse Identification of Posynomial Models
Giuseppe C. Calafiore, Laurent El Ghaoui, Carlo Novara
Posynomials are nonnegative combinations of monomials with possibly fractional and both positive and negative exponents. Posynomial models are widely used in various engineering de…
Approximation Bounds for Sparse Principal Component Analysis
Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui
We produce approximation bounds on a semidefinite programming relaxation for sparse principal component analysis. These bounds control approximation ratios for tractable statistics…
Safe Feature Elimination for the LASSO and Sparse Supervised Learning Problems
Laurent El Ghaoui, Vivian Viallon, Tarek Rabbani
We describe a fast method to eliminate features (variables) in l1 -penalized least-square regression (or LASSO) problems. The elimination of features leads to a potentially substan…
Testing the Nullspace Property using Semidefinite Programming
Alexandre d'Aspremont, Laurent El Ghaoui
Recent results in compressed sensing show that, under certain conditions, the sparsest solution to an underdetermined set of linear equations can be recovered by solving a linear p…
Optimal Solutions for Sparse Principal Component Analysis
Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonzer…