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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 5 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
AIPS
2009
13 years 8 months ago
Lower Bounding Klondike Solitaire with Monte-Carlo Planning
Despite its ubiquitous presence, very little is known about the odds of winning the simple card game of Klondike Solitaire. The main goal of this paper is to investigate the use o...
Ronald Bjarnason, Alan Fern, Prasad Tadepalli
DASFAA
2009
IEEE
133views Database» more  DASFAA 2009»
14 years 2 months ago
Probabilistic Ranking in Uncertain Vector Spaces
Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
HPDC
2002
IEEE
14 years 13 days ago
A Decentralized, Adaptive Replica Location Mechanism
We describe a decentralized, adaptive mechanism for replica location in wide-area distributed systems. Unlike traditional, hierarchical (e.g, DNS) and more recent (e.g., CAN, Chor...
Matei Ripeanu, Ian T. Foster
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 1 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...