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» Learning Generative Models via Discriminative Approaches
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ISMB
1994
13 years 10 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
ICCV
2005
IEEE
14 years 11 months ago
Modeling Scenes with Local Descriptors and Latent Aspects
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
FUZZIEEE
2007
IEEE
14 years 3 months ago
An On-Line Fuzzy Predictor from Real-Time Data
The algorithm of on-line predictor from input-output data pairs will be proposed. In this paper, it proposed an approach to generate fuzzy rules of predictor from real-time input-o...
Chih-Ching Hsiao, Shun-Feng Su
ICML
2005
IEEE
14 years 9 months ago
Learn to weight terms in information retrieval using category information
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
Rong Jin, Joyce Y. Chai, Luo Si
FM
2005
Springer
112views Formal Methods» more  FM 2005»
14 years 2 months ago
Dynamic Component Substitutability Analysis
This paper presents an automated and compositional procedure to solve the substitutability problem in the context of evolving software systems. Our solution contributes two techniq...
Natasha Sharygina, Sagar Chaki, Edmund M. Clarke, ...