In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
In this paper, a new sparse approximation technique is proposed for incremental power grid analysis. Our proposed method is motivated by the observation that when a power grid net...
In Latent Semantic Indexing (LSI), a collection of documents is often pre-processed to form a sparse term-document matrix, followed by a computation of a low-rank approximation to...
Given the increasing traffic on the World Wide Web (Web), it is difficult for a single popular Web server to handle the demand from its many clients. By clustering a group of Web ...
This paper presents a distributed algorithm for wireless adhoc networks that runs in polylogarithmic number of rounds in the size of the network and constructs a lightweight, line...