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NIPS
2003
15 years 8 months ago
Geometric Clustering Using the Information Bottleneck Method
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
Susanne Still, William Bialek, Léon Bottou
IR
2002
15 years 6 months ago
Adaptive Filtering of Newswire Stories using Two-Level Clustering
Adaptive filtering of news is an area of information retrieval gaining substantial interest as services become more available on the Internet. This paper reports on a number of ex...
David Eichmann, Padmini Srinivasan
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
16 years 24 days ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
IV
2005
IEEE
136views Visualization» more  IV 2005»
16 years 23 days ago
Improved Visual Clustering of Large Multi-dimensional Data Sets
Lowering computational cost of data analysis and visualization techniques is an essential step towards including the user in the visualization. In this paper we present an improve...
Eduardo Tejada, Rosane Minghim
AVSS
2007
IEEE
16 years 1 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen