We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse featurebased stereo, and ...
In this paper, we formalize the problem of Basic Graph Pattern (BGP) optimization for SPARQL queries and main memory graph implementations of RDF data. We define and analyze the c...
Markus Stocker, Andy Seaborne, Abraham Bernstein, ...
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Hyper-heuristics (HHs) are heuristics that work with an arbitrary set of search operators or algorithms and combine these algorithms adaptively to achieve a better performance tha...
Retargetable C compilers are nowadays widely used to quickly obtain compiler support for new embedded processors and to perform early processor architecture exploration. One frequ...
Manuel Hohenauer, Christoph Schumacher, Rainer Leu...