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ICML
2005
IEEE
14 years 8 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
CIKM
2008
Springer
13 years 10 months ago
Identifying table boundaries in digital documents via sparse line detection
Most prior work on information extraction has focused on extracting information from text in digital documents. However, often, the most important information being reported in an...
Ying Liu, Prasenjit Mitra, C. Lee Giles
MEDINFO
2007
132views Healthcare» more  MEDINFO 2007»
13 years 9 months ago
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
JMLR
2002
89views more  JMLR 2002»
13 years 7 months ago
A Robust Minimax Approach to Classification
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
PPSN
2010
Springer
13 years 6 months ago
Comparison-Based Optimizers Need Comparison-Based Surrogates
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
Ilya Loshchilov, Marc Schoenauer, Michèle S...