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» Sublinear Optimization for Machine Learning
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ICML
2007
IEEE
14 years 8 months ago
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
Roberto Esposito, Daniele P. Radicioni
ICANN
2001
Springer
14 years 5 days ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
ICPR
2010
IEEE
13 years 7 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
CLEF
2008
Springer
13 years 9 months ago
Combining Logic and Machine Learning for Answering Questions
Abstract. LogAnswer is a logic-oriented question answering system developed by the AI research group at the University of Koblenz-Landau and by the IICS at the University of Hagen....
Ingo Glöckner, Björn Pelzer
SIAMJO
2008
104views more  SIAMJO 2008»
13 years 7 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd