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» A Framework for Multiple-Instance Learning
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ML
2008
ACM
135views Machine Learning» more  ML 2008»
15 years 7 months ago
Compiling pattern matching to good decision trees
We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Luc Maranget
PAMI
2006
147views more  PAMI 2006»
15 years 6 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
166
Voted
JKM
2007
89views more  JKM 2007»
15 years 6 months ago
Knowledge leadership cycles: an approach from Nonaka's viewpoint
Purpose – The aim of this paper is to analyse leadership cycles based on knowledge creation, with learning and culture as key elements for reaching leadership. Following Ikujiro...
Maria Sarabia
JNCA
2007
136views more  JNCA 2007»
15 years 6 months ago
Adaptive anomaly detection with evolving connectionist systems
Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable...
Yihua Liao, V. Rao Vemuri, Alejandro Pasos
JMLR
2002
140views more  JMLR 2002»
15 years 6 months ago
On Boosting with Polynomially Bounded Distributions
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
Nader H. Bshouty, Dmitry Gavinsky