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ECAI
2010
Springer
13 years 6 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes
ICASSP
2008
IEEE
13 years 11 months ago
Learning to satisfy
This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
ICCAD
2009
IEEE
147views Hardware» more  ICCAD 2009»
13 years 3 months ago
SAT-based protein design
Computational protein design can be formulated as an optimization problem, where the objective is to identify the sequence of amino acids that minimizes the energy of a given prot...
Noah Ollikainen, Ellen Sentovich, Carlos Coelho, A...
WWW
2009
ACM
14 years 5 months ago
Combining global optimization with local selection for efficient QoS-aware service composition
The run-time binding of web services has been recently put forward in order to support rapid and dynamic web service compositions. With the growing number of alternative web servi...
Mohammad Alrifai, Thomas Risse
AI
1999
Springer
13 years 4 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...