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» Predicting Time Series with Support Vector Machines
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ACL
2006
15 years 5 months ago
Discriminative Classifiers for Deterministic Dependency Parsing
Deterministic parsing guided by treebankinduced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systemat...
Johan Hall, Joakim Nivre, Jens Nilsson
NIPS
2001
15 years 5 months ago
A Sequence Kernel and its Application to Speaker Recognition
A novel approach for comparing sequences of observations using an explicit-expansion kernel is demonstrated. The kernel is derived using the assumption of the independence of the ...
W. M. Campbell
JMLR
2006
89views more  JMLR 2006»
15 years 3 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
JMLR
2006
143views more  JMLR 2006»
15 years 3 months ago
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...
Régis Vert, Jean-Philippe Vert
ISNN
2010
Springer
15 years 2 months ago
Pruning Training Samples Using a Supervised Clustering Algorithm
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Minzhang Huang, Hai Zhao, Bao-Liang Lu