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» Data structures with dynamical random transitions
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NIPS
2008
13 years 8 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
IJBRA
2007
80views more  IJBRA 2007»
13 years 7 months ago
On predicting secondary structure transition
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
Raja Loganantharaj, Vivek Philip
ICML
2007
IEEE
14 years 8 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
INFOCOM
2005
IEEE
14 years 1 months ago
Fast replication in content distribution overlays
— We present SPIDER – a system for fast replication or distribution of large content from a single source to multiple sites interconnected over Internet or via a private networ...
Samrat Ganguly, Akhilesh Saxena, Sudeept Bhatnagar...
JMLR
2008
159views more  JMLR 2008»
13 years 7 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen