418 citations · 3.5k across the 221 of their papers we have counts for
5 papers · 1 filter
A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control
Adel Bibi, El Houcine Bergou, Ozan Sener +2
We consider the problem of unconstrained minimization of a smooth objective function in in a setting where only function evaluations are possible. While importance sampling…
Improving SAGA via a Probabilistic Interpolation with Gradient Descent
Adel Bibi, Alibek Sailanbayev, Bernard Ghanem +2
We develop and analyze a new algorithm for empirical risk minimization, which is the key paradigm for training supervised machine learning models. Our method---SAGD---is based on a…
A Matrix Splitting Method for Composite Function Minimization
Ganzhao Yuan, Wei-Shi Zheng, Bernard Ghanem
Composite function minimization captures a wide spectrum of applications in both computer vision and machine learning. It includes bound constrained optimization and cardinality re…
Sparsity Constrained Minimization via Mathematical Programming with Equilibrium Constraints
Ganzhao Yuan, Bernard Ghanem
Sparsity constrained minimization captures a wide spectrum of applications in both machine learning and signal processing. This class of problems is difficult to solve since it is…
Binary Optimization via Mathematical Programming with Equilibrium Constraints
Ganzhao Yuan, Bernard Ghanem
Binary optimization is a central problem in mathematical optimization and its applications are abundant. To solve this problem, we propose a new class of continuous optimization te…