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» Performance Modeling of a Cluster of Workstations
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NIPS
2004
14 years 11 months ago
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes
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...
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, ...
BMCBI
2010
145views more  BMCBI 2010»
14 years 10 months ago
Clustering metagenomic sequences with interpolated Markov models
Background: Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and s...
David R. Kelley, Steven L. Salzberg
ICPP
2005
IEEE
15 years 3 months ago
Optimizing Collective Communications on SMP Clusters
We describe a generic programming model to design collective communications on SMP clusters. The programming model utilizes shared memory for collective communications and overlap...
Meng-Shiou Wu, Ricky A. Kendall, Kyle Wright
JMLR
2002
111views more  JMLR 2002»
14 years 9 months ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman
IDA
2007
Springer
14 years 9 months ago
In search of deterministic methods for initializing K-means and Gaussian mixture clustering
The performance of K-means and Gaussian mixture model (GMM) clustering depends on the initial guess of partitions. Typically, clus∗ corresponding author 1
Ting Su, Jennifer G. Dy