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» A Spectral Algorithm for Learning Hidden Markov Models
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JMLR
2010
202views more  JMLR 2010»
14 years 11 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
HUC
2007
Springer
15 years 11 months ago
Tracking Free-Weight Exercises
Weight training, in addition to aerobic exercises, is an important component of a balanced exercise program. However, mechanisms for tracking free weight exercises have not yet bee...
Keng-hao Chang, Mike Y. Chen, John Canny
BMCBI
2008
103views more  BMCBI 2008»
15 years 4 months ago
Parameter estimation for robust HMM analysis of ChIP-chip data
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Peter Humburg, David Bulger, Glenn Stone
142
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ICIP
2001
IEEE
16 years 6 months ago
Automatic multi-modal dialogue scene indexing
An automatic algorithm for indexing dialogue scenes in multimedia content is proposed. The content is segmented into dialogue scenes using the state transitions of a hidden Markov...
A. Aydin Alatan
ECCV
2002
Springer
16 years 6 months ago
Parsing Images into Region and Curve Processes
Abstract. Natural scenes consist of a wide variety of stochastic patterns. While many patterns are represented well by statistical models in two dimensional regions as most image s...
Zhuowen Tu, Song Chun Zhu