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ICML
2010
IEEE
15 years 20 days ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
OL
2011
332views Neural Networks» more  OL 2011»
14 years 6 months ago
A robust implementation of a sequential quadratic programming algorithm with successive error restoration
We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the a...
Klaus Schittkowski
COLT
1998
Springer
15 years 3 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
SODA
2008
ACM
200views Algorithms» more  SODA 2008»
15 years 1 months ago
Clustering for metric and non-metric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P, our goal is to find a set C of size k such that the s...
Marcel R. Ackermann, Johannes Blömer, Christi...
ALT
2008
Springer
15 years 8 months ago
Entropy Regularized LPBoost
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vish...