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CVPR
2007
IEEE
15 years 11 months ago
Learning Generative Models via Discriminative Approaches
Generative model learning is one of the key problems in machine learning and computer vision. Currently the use of generative models is limited due to the difficulty in effective...
Zhuowen Tu
CVPR
2006
IEEE
15 years 10 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 4 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang
BMCBI
2010
133views more  BMCBI 2010»
15 years 4 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
HICSS
2006
IEEE
115views Biometrics» more  HICSS 2006»
15 years 10 months ago
Learning about Interoperability for Emergency Response: Geographic Information Technologies and the World Trade Center Crisis
Geographic information technologies (GIT) have the potential to integrate information among multiple organizations. In fact, some of the most impressive advantages of using geo-sp...
Teresa M. Harrison, José Ramón Gil-G...