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» Hidden Markov Support Vector Machines
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NIPS
2003
14 years 3 days ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
WABI
2009
Springer
155views Bioinformatics» more  WABI 2009»
14 years 5 months ago
A Markov Classification Model for Metabolic Pathways
Background: This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first ide...
Timothy Hancock, Hiroshi Mamitsuka
KES
2007
Springer
14 years 4 months ago
Time Discretisation Applied to Anomaly Detection in a Marine Engine
This paper introduces the problems associated with anomaly detection in a marine engine, and explains the benefits that the SAX representation brings to the field. Despite limita...
Ian Morgan, Honghai Liu, George Turnbull, David J....
ECML
2006
Springer
14 years 2 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
IJDMB
2011
85views more  IJDMB 2011»
13 years 5 months ago
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation
: Classification methods are vital for efficient access of knowledge hidden in biomedical publications. Support vector machines (SVMs) are modern non-parametric deterministic clas...
Tamara Polajnar, Simon Rogers, Mark Girolami