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EUROPAR
2004
Springer
15 years 1 months ago
Efficient Parallel Hierarchical Clustering
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...
ICMLA
2003
14 years 11 months ago
Reinforcement Learning Task Clustering
This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
James L. Carroll, Todd S. Peterson, Kevin D. Seppi
ECCV
2004
Springer
15 years 11 months ago
Parallel Variational Motion Estimation by Domain Decomposition and Cluster Computing
We present an approach to parallel variational optical flow computation on standard hardware by domain decomposition. Using an arbitrary partition of the image plane into rectangul...
Timo Kohlberger, Christoph Schnörr, Andr&eacu...
BMCBI
2008
142views more  BMCBI 2008»
14 years 9 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
COLT
2005
Springer
15 years 3 months ago
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivated...
Mikhail Belkin, Partha Niyogi