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Mathematical and Engineering Methods in Computer Science = 10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Mathematical and Engineering Methods in Computer Science/ edited by Jan Kofroň, Tomáš Vojnar.
其他題名:
10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers /
其他作者:
Kofroň, Jan.
面頁冊數:
IX, 157 p. 51 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Software engineering. -
電子資源:
https://doi.org/10.1007/978-3-319-29817-7
ISBN:
9783319298177
Mathematical and Engineering Methods in Computer Science = 10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers /
Mathematical and Engineering Methods in Computer Science
10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers /[electronic resource] :edited by Jan Kofroň, Tomáš Vojnar. - 1st ed. 2016. - IX, 157 p. 51 illus. in color.online resource. - Programming and Software Engineering ;9548. - Programming and Software Engineering ;8987.
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.
This volume contains the post-conference proceedings of the 10th Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2015, held in Telč, Czech Republic, in October 2015. 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.).<ioinformatics, recommender="" systems,="" high-performance="" and="" cloud="" computing,="" non-traditional="" computational="" models="" (quantum="" etc.).
ISBN: 9783319298177
Standard No.: 10.1007/978-3-319-29817-7doiSubjects--Topical Terms:
562952
Software engineering.
LC Class. No.: QA76.758
Dewey Class. No.: 005.1
Mathematical and Engineering Methods in Computer Science = 10th International Doctoral Workshop, MEMICS 2015, Telč, Czech Republic, October 23-25, 2015, Revised Selected Papers /
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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.
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