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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 7 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
16 years 9 days ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg
192
Voted
GECCO
2010
Springer
148views Optimization» more  GECCO 2010»
15 years 11 months ago
Guarding against premature convergence while accelerating evolutionary search
The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that gu...
Josh C. Bongard, Gregory S. Hornby
GECCO
2009
Springer
119views Optimization» more  GECCO 2009»
15 years 11 months ago
Cooperative micro-differential evolution for high-dimensional problems
High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their ...
Konstantinos E. Parsopoulos
IS
2007
15 years 6 months ago
Mining association rules in very large clustered domains
Emerging applications introduce the requirement for novel association-rule mining algorithms that will be scalable not only with respect to the number of records (number of rows) ...
Alexandros Nanopoulos, Apostolos N. Papadopoulos, ...