Titlebook: KI 2013: Advances in Artificial Intelligence; 36th Annual German C Ingo J. Timm,Matthias Thimm Conference proceedings 2013 Springer-Verlag

愛花花兒憤怒

On GPU-Based Nearest Neighbor Queries for Large-Scale Photometric Catalogs in Astronomy,text. Our experiments indicate that carefully tuned implementations of spatial search structures for such multi-core devices can significantly reduce the practical runtime. This renders the resulting frameworks an important algorithmic tool for current and upcoming data analyses in astronomy.

Abbreviate

Variable Neighborhood Search for Continuous Monitoring Problem with Inter-Depot Routes,timum. Furthermore, the proposed algorithm outperforms existing methods for the Continuous Monitoring Problem (CMP) in both solution quality (in 3 times) and computational time (more than 400 times faster).

主動(dòng)

extinct

Comparison of Sensor-Feedback Prediction Methods for Robust Behavior Execution,d sensor output. Two function fitting approaches (analytic model and generic function approximation) and a vector quantization method are compared with each other. The evaluation of the triggering mechanism in real scenarios will show that the execution of emergency actions in unexpected situations

Veneer

責(zé)怪

https://doi.org/10.1007/978-3-642-40942-4clustering; human motion; machine learning; modeling; semantics

Inflated

978-3-642-40941-7Springer-Verlag Berlin Heidelberg 2013

代理人

KI 2013: Advances in Artificial Intelligence978-3-642-40942-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

矛盾

Advances in Accessing Big Data with Expressive Ontologies,cations. Recently, advances for the expressive DL . have been made in the dissertation of S. Wandelt for concept-based instance retrieval on Big Data descriptions stored in secondary memory. In this paper we extend this approach by investigating optimization algorithms for answering grounded conjunctive queries.

四目在模仿

Changes of Relational Probabilistic Belief States and Their Computation under Optimum Entropy Semanstic belief states by use of the relative entropy in a propositional setting to relational languages. As a second contribution of this paper, we present a method to compute such belief changes by considering a dual problem and present first application and experimental results.