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IJCAI
2007
14 years 11 months ago
Collapsed Variational Dirichlet Process Mixture Models
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
Kenichi Kurihara, Max Welling, Yee Whye Teh
SDM
2007
SIAM
139views Data Mining» more  SDM 2007»
14 years 11 months ago
Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
We present an efficient dynamic algorithm for clustering undirected graphs, whose edge property is changing continuously. The algorithm maintains clusters of high quality in pres...
Barna Saha, Pabitra Mitra
ASUNAM
2009
IEEE
15 years 2 months ago
Mining the Dynamics of Music Preferences from a Social Networking Site
In this paper we present an application of our incremental graph clustering algorithm (DENGRAPH) on a data set obtained from the music community site Last.fm. The aim of our study...
Nico Schlitter, Tanja Falkowski
APIN
1999
107views more  APIN 1999»
14 years 9 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
MICCAI
2006
Springer
15 years 10 months ago
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
Hal S. Stern, Padhraic Smyth, Seyoung Kim