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BMCBI
2002
133views more  BMCBI 2002»
15 years 1 months ago
Identification and characterization of subfamily-specific signatures in a large protein superfamily by a hidden Markov model app
Background: Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include ...
Kevin Truong, Mitsuhiko Ikura
ICML
2003
IEEE
16 years 2 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
CVPR
2009
IEEE
16 years 9 months ago
A Similarity Measure Between Vector Sequences with Application to Handwritten Word Image Retrieval
This article proposes a novel similarity measure between vector sequences. Recently, a model-based approach was introduced to address this issue. It consists in modeling each se...
José A. Rodríguez-Serrano, Florent P...
113
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HPCS
2005
IEEE
15 years 7 months ago
Parallel Lattice Implementation for Option Pricing under Mixed State-Dependent Volatility Models
— With the principal goal of developing an alternative, relatively simple and tractable pricing framework for accurately reproducing a market implied volatility surface, this pap...
Giuseppe Campolieti, Roman Makarov
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 6 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani