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» A general model for clustering binary data
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ECCV
2008
Springer
14 years 9 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
ICALP
2009
Springer
14 years 8 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
13 years 11 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
ISCAPDCS
2004
13 years 9 months ago
A VFSA Scheduler for Radiative Transfer Data in Climate Models
Scheduling and load-balancing techniques play an integral role in reducing the overall execution time of scientific applications on clustered multi-node systems. The increasing co...
S. P. Muszala, Gita Alaghband, Daniel A. Connors, ...
CAIP
2009
Springer
114views Image Analysis» more  CAIP 2009»
13 years 11 months ago
Decision Trees Using the Minimum Entropy-of-Error Principle
Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estim...
Joaquim Marques de Sá, João Gama, Ra...