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» Support Vector Machine for Multiple Feature Classifcation
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IJCAI
2007
13 years 10 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
14 years 1 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
GPEM
2008
128views more  GPEM 2008»
13 years 9 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
ECML
2006
Springer
14 years 29 days 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
SG
2010
Springer
14 years 1 months ago
Sketch-Based Interfaces: Exploiting Spatio-temporal Context for Automatic Stroke Grouping
In this paper, we investigate how discourse context in the form of short-term memory can be exploited to automatically group consecutive strokes in digital freehand sketching. With...
Lutz Dickmann, Tobias Lensing, Robert Porzel, Rain...