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ICML
2010
IEEE
15 years 8 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
HEURISTICS
2008
153views more  HEURISTICS 2008»
15 years 7 months ago
Bringing order into the neighborhoods: relaxation guided variable neighborhood search
In this article we investigate a new variant of Variable Neighborhood Search (VNS): Relaxation Guided Variable Neighborhood Search. It is based on the general VNS scheme and a new...
Jakob Puchinger, Günther R. Raidl
EOR
2006
134views more  EOR 2006»
15 years 7 months ago
A smoothing heuristic for a bilevel pricing problem
In this paper, we provide a heuristic procedure, that performs well from a global optimality point of view, for an important and difficult class of bilevel programs. The algorithm...
Jean-Pierre Dussault, Patrice Marcotte, Séb...
DSP
2007
15 years 7 months ago
Knowledge based adaptive processing for ground moving target indication
This paper presents a preliminary knowledge based approach to Space-Time Adaptive Processing (STAP) for ground moving target indication from an airborne platform. The KB-processor...
Raviraj Adve, Todd Hale, Michael C. Wicks
EOR
2007
95views more  EOR 2007»
15 years 7 months ago
A hybrid genetic algorithm for the two-dimensional single large object placement problem
In the two-dimensional single large object placement problem, we are given a rectangular master surface which has to be cut into a set of smaller rectangular items, with the aim o...
Eleni Hadjiconstantinou, Manuel Iori