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SSPR
2010
Springer
13 years 5 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
ACL
2011
12 years 11 months ago
Gappy Phrasal Alignment By Agreement
We propose a principled and efficient phraseto-phrase alignment model, useful in machine translation as well as other related natural language processing problems. In a hidden se...
Mohit Bansal, Chris Quirk, Robert C. Moore
ECML
2005
Springer
14 years 28 days ago
Inducing Hidden Markov Models to Model Long-Term Dependencies
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Jérôme Callut, Pierre Dupont
ICASSP
2010
IEEE
13 years 7 months ago
Variational nonparametric Bayesian Hidden Markov Model
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...
Nan Ding, Zhijian Ou
PERCOM
2009
ACM
14 years 2 months ago
Markov Chain Existence and Hidden Markov Models in Spectrum Sensing
—The primary function of a cognitive radio is to detect idle frequencies or sub-bands, not used by the primary users (PUs), and allocate these frequencies to secondary users. The...
Chittabrata Ghosh, Carlos de M. Cordeiro, Dharma P...