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BMCBI
2002
133views more  BMCBI 2002»
14 years 9 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
15 years 10 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 4 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...
HPCS
2005
IEEE
15 years 3 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 1 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