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ICML
2009
IEEE
14 years 8 months ago
Unsupervised hierarchical modeling of locomotion styles
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
Wei Pan, Lorenzo Torresani
CIBCB
2005
IEEE
14 years 1 months ago
Toward Protein Structure Analysis with Self-Organizing Maps
- Establishing structure-function relationships on the proteomic scale is a unique challenge faced by bioinformatics and molecular biosciences. Large protein families represent nat...
Lutz Hamel, Gongqin Sun, Jing Zhang
CVPR
2010
IEEE
14 years 24 days ago
Anatomical Parts-Based Regression Using Non-Negative Matrix Factorization
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
Swapna Joshi, Karthikeyan Shanmugavadivel, B.S. Ma...
ML
1998
ACM
139views Machine Learning» more  ML 1998»
13 years 7 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
UAI
2004
13 years 9 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer