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» Machine-Learning Applications of Algorithmic Randomness
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GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
13 years 11 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro
ICML
2008
IEEE
14 years 8 months ago
Fast estimation of first-order clause coverage through randomization and maximum likelihood
In inductive logic programming, subsumption is a widely used coverage test. Unfortunately, testing -subsumption is NP-complete, which represents a crucial efficiency bottleneck fo...
Filip Zelezný, Ondrej Kuzelka
ECML
2006
Springer
13 years 11 months ago
Multiple-Instance Learning Via Random Walk
This paper presents a decoupled two stage solution to the multiple-instance learning (MIL) problem. With a constructed affinity matrix to reflect the instance relations, a modified...
Dong Wang, Jianmin Li, Bo Zhang
ICML
1994
IEEE
13 years 11 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
COMBINATORICA
2010
13 years 5 months ago
A randomized embedding algorithm for trees
In this paper, we propose a simple and natural randomized algorithm to embed a tree T in a given graph G. The algorithm can be viewed as a "self-avoiding tree-indexed random ...
Benny Sudakov, Jan Vondrák