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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
WAIM
2009
Springer
14 years 2 months ago
SLICE: A Novel Method to Find Local Linear Correlations by Constructing Hyperplanes
Finding linear correlations in dataset is an important data mining task, which can be widely applied in the real world. Existing correlation clustering methods combine clustering w...
Liang Tang, Changjie Tang, Lei Duan, Yexi Jiang, J...
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 9 months ago
A study of NK landscapes' basins and local optima networks
We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces [5]. We use the well-known fami...
Gabriela Ochoa, Marco Tomassini, Sébastien ...
KER
2007
90views more  KER 2007»
13 years 8 months ago
PLTOOL: A knowledge engineering tool for planning and learning
AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will tra...
Susana Fernández, Daniel Borrajo, Raquel Fu...
CIAC
2000
Springer
105views Algorithms» more  CIAC 2000»
14 years 12 days ago
Algorithms for a Simple Point Placement Problem
We consideralgorithms for a simple one-dimensionalpoint placement problem: given N points on a line, and noisy measurements of the distances between many pairs of them, estimate th...
Joshua Redstone, Walter L. Ruzzo