no code implementations • NeurIPS 2020 • Agniva Chowdhury, Palma London, Haim Avron, Petros Drineas
Linear programming (LP) is used in many machine learning applications, such as $\ell_1$-regularized SVMs, basis pursuit, nonnegative matrix factorization, etc.
no code implementations • 17 Nov 2017 • Palma London, Shai Vardi, Adam Wierman, Hanling Yi
This paper presents an acceleration framework for packing linear programming problems where the amount of data available is limited, i. e., where the number of constraints m is small compared to the variable dimension n. The framework can be used as a black box to speed up linear programming solvers dramatically, by two orders of magnitude in our experiments.
no code implementations • 28 Feb 2014 • Kean Ming Tan, Palma London, Karthik Mohan, Su-In Lee, Maryam Fazel, Daniela Witten
We consider the problem of learning a high-dimensional graphical model in which certain hub nodes are highly-connected to many other nodes.
no code implementations • 21 Mar 2013 • Karthik Mohan, Palma London, Maryam Fazel, Daniela Witten, Su-In Lee
We consider estimation under two distinct assumptions: (1) differences between the K networks are due to individual nodes that are perturbed across conditions, or (2) similarities among the K networks are due to the presence of common hub nodes that are shared across all K networks.
