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» Conditional Random Fields for Transmembrane Helix Prediction
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NIPS
2008
13 years 7 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
ECCV
2006
Springer
14 years 8 months ago
Figure/Ground Assignment in Natural Images
Abstract. Figure/ground assignment is a key step in perceptual organization which assigns contours to one of the two abutting regions, providing information about occlusion and all...
Xiaofeng Ren, Charless Fowlkes, Jitendra Malik
BMCBI
2008
153views more  BMCBI 2008»
13 years 6 months ago
Estimating the size of the solution space of metabolic networks
Background: Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network...
Alfredo Braunstein, Roberto Mulet, Andrea Pagnani
WWW
2008
ACM
14 years 6 months ago
Learning transportation mode from raw gps data for geographic applications on the web
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning kno...
Yu Zheng, Like Liu, Longhao Wang, Xing Xie
ACL
2006
13 years 7 months ago
An Effective Two-Stage Model for Exploiting Non-Local Dependencies in Named Entity Recognition
This paper shows that a simple two-stage approach to handle non-local dependencies in Named Entity Recognition (NER) can outperform existing approaches that handle non-local depen...
Vijay Krishnan, Christopher D. Manning