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JMLR
2008
133views more  JMLR 2008»
15 years 6 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
152
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JUCS
2008
208views more  JUCS 2008»
15 years 6 months ago
Using Taxonomies to Support the Macro Design Process for the Production of Web Based Trainings
: Recently Web Based Training (WBT) starts to be widely used as a new way of teaching. Unfortunately, this mode of teaching imposes new requirements and constraints. It has made th...
Abdelhak Aqqal, Christoph Rensing, Ralf Steinmetz,...
JMLR
2006
116views more  JMLR 2006»
15 years 6 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
ESWA
2007
117views more  ESWA 2007»
15 years 6 months ago
An HMM for detecting spam mail
Hidden Markov Models, or HMMs for short, have been recently used in Bioinformatics for the classification of DNA or protein chains, giving rise to what is known as Profile Hidde...
José Gordillo, Eduardo Conde
PAMI
2008
175views more  PAMI 2008»
15 years 6 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
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