TSMC
2010
13 years 6 months ago
2010
Abstract--It is critical to use automated generators for synthetic models and data, given the sparsity of benchmark models for empirical analysis and the cost of generating models ...
ICDM
2009
IEEE
13 years 9 months ago
2009
IEEE
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
IJCV
2000
13 years 11 months ago
2000
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
DMIN
2006
14 years 25 days ago
2006
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
FORTE
2008
14 years 27 days ago
2008
Abstract. Model generation is an important formal technique for finding interesting instances of computationally hard problems. In this paper we study model generation over Horn lo...
COMPSAC
2002
IEEE
14 years 4 months ago
2002
IEEE
With computer systems becoming ever larger and more complex, the cost and effort associated with their construction is increasing and the systems are now sufficiently complex that...
ICMT
2009
Springer
14 years 6 months ago
2009
Springer
Testing model transformations requires input models which are graphs of inter-connected objects that must conform to a meta-model and meta-constraints from heterogeneous sources su...
ICFEM
2009
Springer
14 years 6 months ago
2009
Springer
Abstract. We study the problem of generating a database and parameters for a given parameterized SQL query satisfying a given test condition. We introduce a formal background theor...