Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
Abstract. We study two-stage robust variants of combinatorial optimization problems like Steiner tree, Steiner forest, and uncapacitated facility location. The robust optimization ...
Rohit Khandekar, Guy Kortsarz, Vahab S. Mirrokni, ...
In the typical nonparametric approach to classification in instance-based learning and data mining, random data (the training set of patterns) are collected and used to design a d...
Binay K. Bhattacharya, Kaustav Mukherjee, Godfried...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Abstract. We describe a novel approach for constructing a single spanning tree for data aggregation towards a sink node. The tree is universal in the sense that it is static and in...
Srinivasagopalan Srivathsan, Costas Busch, S. Sith...