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» Approximation schemes for clustering problems
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SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
15 years 6 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
ICALP
2010
Springer
15 years 2 months ago
Clustering with Diversity
Abstract. We consider the clustering with diversity problem: given a set of colored points in a metric space, partition them into clusters such that each cluster has at least point...
Jian Li, Ke Yi, Qin Zhang
UAI
2000
14 years 11 months ago
Value-Directed Belief State Approximation for POMDPs
We consider the problem belief-state monitoring for the purposes of implementing a policy for a partially-observable Markov decision process (POMDP), specifically how one might ap...
Pascal Poupart, Craig Boutilier
AAAI
2007
14 years 12 months ago
Approximate Counting by Sampling the Backtrack-free Search Space
We present a new estimator for counting the number of solutions of a Boolean satisfiability problem as a part of an importance sampling framework. The estimator uses the recently...
Vibhav Gogate, Rina Dechter
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
15 years 10 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li