Abstract Approximate simulation relations have recently been introduced as a powerful tool for the approximation of discrete and continuous systems. In this paper, we his abstracti...
Background: Feature selection is an important pre-processing task in the analysis of complex data. Selecting an appropriate subset of features can improve classification or cluste...
Assaf Gottlieb, Roy Varshavsky, Michal Linial, Dav...
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
We give an implementation of the Goemans-Williamson clustering procedure which is at the core of several approximation algorithms including those for Generalized Steiner Trees, Pr...
Richard Cole, Ramesh Hariharan, Moshe Lewenstein, ...
We describe a simple random-sampling based procedure for producing sparse matrix approximations. Our procedure and analysis are extremely simple: the analysis uses nothing more th...