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» Co-Tracking Using Semi-Supervised Support Vector Machines
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111
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ICASSP
2009
IEEE
15 years 6 months ago
High-level feature extraction using SVM with walk-based graph kernel
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
Jean-Philippe Vert, Tomoko Matsui, Shin'ichi Satoh...
155
Voted
CLEF
2011
Springer
14 years 2 months ago
Author Identification Using Semi-supervised Learning - Notebook for PAN at CLEF 2011
Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while in...
Ioannis Kourtis, Efstathios Stamatatos
110
Voted
ESANN
2008
15 years 4 months ago
Survival SVM: a practical scalable algorithm
This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
133
Voted
ACL
2006
15 years 4 months ago
Automatic Learning of Textual Entailments with Cross-Pair Similarities
In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to ...
Fabio Massimo Zanzotto, Alessandro Moschitti
120
Voted
ICASSP
2009
IEEE
15 years 12 days ago
Phonological features in discriminative classification of dysarthric speech
In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models fo...
Frank Rudzicz