24 search results - page 2 / 5 » Using machine learning to make constraint solver implementat... |
CONSTRAINTS
2006
13 years 4 months ago
2006
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs conta...
AAAI
2008
13 years 7 months ago
2008
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
KDD
2004
ACM
14 years 5 months ago
2004
ACM
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
LCTRTS
2007
Springer
13 years 11 months ago
2007
Springer
Embedded systems serve an emerging and diverse set of applications. As a result, more computational and storage capabilities are added to accommodate ever more demanding applicati...
AIEDAM
1998
13 years 4 months ago
1998
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...