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» Minimization and Partitioning Method Reducing Input Sets
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130
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ALMOB
2006
89views more  ALMOB 2006»
15 years 1 months ago
On the maximal cliques in c-max-tolerance graphs and their application in clustering molecular sequences
Given a set S of n locally aligned sequences, it is a needed prerequisite to partition it into groups of very similar sequences to facilitate subsequent computations, such as the ...
Katharina Anna Lehmann, Michael Kaufmann, Stephan ...
IPPS
2010
IEEE
14 years 11 months ago
On the parallelisation of MCMC-based image processing
Abstract--The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov C...
Jonathan M. R. Byrd, Stephen A. Jarvis, Abhir H. B...
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 2 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
TOG
2002
102views more  TOG 2002»
15 years 1 months ago
Hierarchical pattern mapping
We present a multi-scale algorithm for mapping a texture defined by an input image onto an arbitrary surface. It avoids the generation and storage of a new, specific texture. The ...
Cyril Soler, Marie-Paule Cani, Alexis Angelidis
159
Voted
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
14 years 11 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava