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ML
1998
ACM
139views Machine Learning» more  ML 1998»
13 years 7 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby

Book
412views
15 years 6 months ago
Algorithms for Clustering Data
"Cluster analysis is an important technique in the rapidly growing field known as exploratory data analysis and is being applied in a variety of engineering and scientific dis...
A. K. Jain, R. C. Dubes
DAWAK
2006
Springer
13 years 11 months ago
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...
CVPR
2007
IEEE
14 years 9 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
ICPP
2008
IEEE
14 years 1 months ago
Mapping Algorithms for Multiprocessor Tasks on Multi-Core Clusters
In this paper, we explore the use of hierarchically structured multiprocessor tasks (M-tasks) for programming multi-core cluster systems. These systems often have hierarchically s...
Jörg Dümmler, Thomas Rauber, Gudula R&uu...