Mathematical and engineering methods...
Clark Conference ((2005 :)

 

  • Mathematical and engineering methods in computer science[electronic resource] :10th International Doctoral Workshop, MEMICS 2015, Telc, Czech Republic, October 23-25, 2015 : revised selected papers /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 004
    書名/作者: Mathematical and engineering methods in computer science : 10th International Doctoral Workshop, MEMICS 2015, Telc, Czech Republic, October 23-25, 2015 : revised selected papers // edited by Jan Kofron, Tomas Vojnar.
    其他題名: MEMICS 2015
    其他作者: Kofron, Jan.
    團體作者: Clark Conference
    出版者: Cham : : Springer International Publishing :, 2016.
    面頁冊數: ix, 157 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Information Systems Applications (incl. Internet)
    標題: Computational Biology/Bioinformatics.
    標題: Computer science
    標題: Computer science - Periodicals. - Mathematics
    標題: Software engineering
    標題: Artificial intelligence
    標題: Computer Science.
    標題: Software Engineering.
    標題: Computer Communication Networks.
    標題: Algorithm Analysis and Problem Complexity.
    標題: Management of Computing and Information Systems.
    ISBN: 9783319298177
    ISBN: 9783319298160
    內容註: 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.
    電子資源: http://dx.doi.org/10.1007/978-3-319-29817-7
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