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» Hidden Markov Models with Multiple Observation Processes
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UAI
2008
15 years 1 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
NAR
2006
164views more  NAR 2006»
14 years 11 months ago
FISH - family identification of sequence homologues using structure anchored hidden Markov models
The FISH server is highly accurate in identifying the family membership of domains in a query protein sequence, even in the case of very low sequence identities to known homologue...
Jeanette Tångrot, Lixiao Wang, Bo Kågs...
ICIAP
2007
ACM
15 years 12 months ago
Sparseness Achievement in Hidden Markov Models
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
Manuele Bicego, Marco Cristani, Vittorio Murino
NAACL
1994
15 years 1 months ago
Japanese Word Segmentation by Hidden Markov Model
The processing of Japanese text is complicated by the fact that there are no word delimiters. To segment Japanese text, systems typically use knowledge-based methods and large lex...
Constantine Papageorgiou
IPCV
2010
14 years 9 months ago
Video Action Recognition Using Residual Vector Quantization and Hidden Markov Models
In this paper, we discuss usage of a multi-stage Residual Vector Quantization (RVQ) strategy for human action recognition. To the best of our knowledge, this is the first reported...
Salman Aslam, Christopher F. Barnes, Aaron F. Bobi...