104 search results - page 7 / 21 » Hierarchical Hardness Models for SAT |
CCGRID
2007
IEEE
14 years 2 months ago
2007
IEEE
In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, d...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
CP
2006
Springer
14 years 4 days ago
2006
Springer
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
RECOMB
2010
Springer
14 years 2 months ago
2010
Springer
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
ECP
1997
Springer
14 years 18 days ago
1997
Springer
In this paper we describe SINERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world...