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» Learning a Generative Model for Structural Representations
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ISMB
1994
15 years 3 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
116
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IADIS
2003
15 years 3 months ago
Generating Guided Tours over Indexed Information Resources
This article proposes an approach to the generation of guided tours over indexed information resources on user demand. It represents an alternative to more sophisticated hyperdocu...
Benjamin Buffereau, Pierre Duchet, Philippe Picoue...
107
Voted
CVPR
2008
IEEE
16 years 4 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
16 years 2 months ago
Keyword search on structured and semi-structured data
Empowering users to access databases using simple keywords can relieve the users from the steep learning curve of mastering a structured query language and understanding complex a...
Yi Chen, Wei Wang 0011, Ziyang Liu, Xuemin Lin
ISMIR
2004
Springer
118views Music» more  ISMIR 2004»
15 years 7 months ago
Learning to Align Polyphonic Music
We describe an efficient learning algorithm for aligning a symbolic representation of a musical piece with its acoustic counterpart. Our method employs a supervised learning appr...
Shai Shalev-Shwartz, Joseph Keshet, Yoram Singer