Mathematical and Engineering Methods in Computer Science: 10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers: Lecture Notes in Computer Science, cartea 9548
Editat de Jan Kofroň, Tomáš Vojnaren Limba Engleză Paperback – 4 feb 2016
The 10 thoroughly revised full papers were carefully selected out of 25 submissions and are presented together with 3 invited papers. The topics covered include: security and safety, bioinformatics, recommender systems, high-performance and cloud computing, and non-traditional computational models (quantum computing, etc.).
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Specificații
ISBN-13: 9783319298160
ISBN-10: 331929816X
Pagini: 157
Ilustrații: IX, 157 p. 51 illus. in color.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.25 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Programming and Software Engineering
Locul publicării:Cham, Switzerland
ISBN-10: 331929816X
Pagini: 157
Ilustrații: IX, 157 p. 51 illus. in color.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.25 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Programming and Software Engineering
Locul publicării:Cham, Switzerland
Cuprins
Programming Support for Future Parallel Architectures.- Flexible Interpolation for Efficient Model Checking.- Understanding Transparent and Complicated Users as Instances of Preference Learning for Recommender Systems.- Span-Program-Based Quantum Algorithms for Graph Bipartiteness and Connectivity.- Fitting Aggregation Operators.- Practical Exhaustive Generation of Small Multiway Cuts in Sparse Graphs.- Self-adaptive Architecture for Multi-sensor Embedded Vision System.-
Exceptional Configurations of Quantum Walks with Grover's Coin.- Performance Analysis of Distributed Stream Processing Applications Through Colored Petri Nets.- GPU-Accelerated Real-Time Mesh Simplification Using Parallel Half Edge Collapses.- Classifier Ensemble by Semi-supervised Learning: Local Aggregation Methodology.- The Challenge of Increasing Safe Response of Antivirus Software Users.- Weak Memory Models as LLVM-to-LLVM Transformations.
Caracteristici
Includes supplementary material: sn.pub/extras