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» Learning with Rigorous Support Vector Machines
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JMLR
2011
148views more  JMLR 2011»
14 years 11 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
EACL
2006
ACL Anthology
15 years 5 months ago
Making Tree Kernels Practical for Natural Language Learning
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
Alessandro Moschitti
128
Voted
ICML
2006
IEEE
16 years 4 months ago
Concept boundary detection for speeding up SVMs
Support Vector Machines (SVMs) suffer from an O(n2 ) training cost, where n denotes the number of training instances. In this paper, we propose an algorithm to select boundary ins...
Navneet Panda, Edward Y. Chang, Gang Wu
136
Voted
BMCBI
2008
114views more  BMCBI 2008»
15 years 4 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
ICML
2009
IEEE
16 years 4 months ago
Ranking interesting subgroups
Subgroup discovery is the task of identifying the top k patterns in a database with most significant deviation in the distribution of a target attribute Y . Subgroup discovery is ...
Stefan Rueping