no code implementations • 4 Sep 2019 • Jacob Rafati, Roummel F. Marcia
Quasi-Newton methods, like SGD, require only first-order gradient information, but they can result in superlinear convergence, which makes them attractive alternatives to SGD.
no code implementations • 6 Nov 2018 • Jacob Rafati, Roummel F. Marcia
Deep Reinforcement Learning algorithms require solving a nonconvex and nonlinear unconstrained optimization problem.
no code implementations • 1 Jul 2018 • Jennifer B. Erway, Joshua Griffin, Roummel F. Marcia, Riadh Omheni
Machine learning (ML) problems are often posed as highly nonlinear and nonconvex unconstrained optimization problems.
no code implementations • 26 Jun 2013 • Zachary T. Harmany, Roummel F. Marcia, Rebecca M. Willett
This paper describes a coded aperture and keyed exposure approach to compressive video measurement which admits a small physical platform, high photon efficiency, high temporal resolution, and fast reconstruction algorithms.