NIPS
2003
13 years 6 months ago
2003
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
NIPS
2004
13 years 6 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
UAI
2008
13 years 6 months ago
2008
Exemplar-based clustering methods have been shown to produce state-of-the-art results on a number of synthetic and real-world clustering problems. They are appealing because they ...
FSTTCS
2009
Springer
13 years 9 months ago
2009
Springer
We introduce a graph clustering problem motivated by a stream processing application. Input to our problem is an undirected graph with vertex and edge weights. A cluster is a subse...
ICALP
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. In this paper we present a novel analysis of a random sampling approach for three clustering problems in metric spaces: k-median, min-sum kclustering, and balanced k-medi...
PODS
2006
ACM
14 years 4 months ago
2006
ACM
We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to speci...