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» Training structural svms with kernels using sampled cuts
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KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 5 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
13 years 11 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
ICPR
2004
IEEE
14 years 5 months ago
Tangent Vector Kernels for Invariant Image Classification with SVMs
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
Alexei Pozdnoukhov, Samy Bengio
MINENET
2006
ACM
13 years 10 months ago
SVM learning of IP address structure for latency prediction
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Robert Beverly, Karen R. Sollins, Arthur Berger
PAA
2002
13 years 4 months ago
Combining Discriminant Models with New Multi-Class SVMs
: The idea of performing model combination, instead of model selection, has a long theoretical background in statistics. However, making use of theoretical results is ordinarily su...
Yann Guermeur