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» Tangent Distance Kernels for Support Vector Machines
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JMLR
2010
115views more  JMLR 2010»
13 years 2 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
IWBRS
2005
Springer
145views Biometrics» more  IWBRS 2005»
14 years 1 months ago
Face Authentication Using One-Class Support Vector Machines
Abstract. This paper proposes a new method for personal identity verification based the analysis of face images applying One Class Support Vector Machines. This is a recently intr...
Manuele Bicego, Enrico Grosso, Massimo Tistarelli
ICTAI
2010
IEEE
13 years 5 months ago
Support Vector Methods for Sentence Level Machine Translation Evaluation
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as B...
Antoine Veillard, Elvina Melissa, Cassandra Theodo...
IJCAI
2007
13 years 9 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
IJCNN
2008
IEEE
14 years 1 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe