We investigate under what conditions clustering by learning a mixture of spherical Gaussians is (a) computationally tractable; and (b) statistically possible. We show that using p...
Nathan Srebro, Gregory Shakhnarovich, Sam T. Rowei...
In this paper, we examine the application of manifold learning to the clustering problem. The method used is Locality Preserving Projections (LPP), which is chosen because of its ...
Hassan A. Kingravi, M. Emre Celebi, Pragya P. Raja...
Entity Resolution (ER) is an important real world problem that has attracted significant research interest over the past few years. It deals with determining which object descript...
Zhaoqi Chen, Dmitri V. Kalashnikov, Sharad Mehrotr...
In the present paper we explain the basic ideas of Robust Perron Cluster Analysis (PCCA+) and exemplify the different application areas of this new and powerful method. Recently, ...
We present two modifications to the popular k-means clustering algorithm to address the extreme requirements for latency, scalability, and sparsity encountered in user-facing web...