In this paper we present a new approach for curve clustering designed for analysis of spatiotemporal data. Such kind of data contains both spatial and temporal patterns that we de...
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...
Assume a uniform, multidimensional grid of bivariate data, where each cell of the grid has a count ci and a baseline bi. Our goal is to find spatial regions (d-dimensional rectang...
Daniel B. Neill, Andrew W. Moore, Francisco Pereir...