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» Learning from Highly Structured Data by Decomposition
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BMCBI
2010
144views more  BMCBI 2010»
14 years 10 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
ML
1998
ACM
139views Machine Learning» more  ML 1998»
14 years 10 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
76
Voted
ACMSE
2007
ACM
15 years 2 months ago
Verifying design modularity, hierarchy, and interaction locality using data clustering techniques
Modularity, hierarchy, and interaction locality are general approaches to reducing the complexity of any large system. A widely used principle in achieving these goals in designin...
Liguo Yu, Srini Ramaswamy
84
Voted
TMI
2010
165views more  TMI 2010»
14 years 8 months ago
Spatio-Temporal Data Fusion for 3D+T Image Reconstruction in Cerebral Angiography
—This paper provides a framework for generating high resolution time sequences of 3D images that show the dynamics of cerebral blood flow. These sequences have the potential to ...
Andrew Copeland, Rami Mangoubi, Mukund N. Desai, S...
98
Voted
OGAI
1993
15 years 2 months ago
Combining Neural Networks and Fuzzy Controllers
Fuzzy controllers are designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory ...
Detlef Nauck, Frank Klawonn, Rudolf Kruse