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Computational mathematics
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#	Item
81	Weighted Synergy Graphs for Effective Team Formation with Heterogeneous Ad Hoc Agents Somchaya Liemhetcharat∗ and Manuela Veloso School of Computer Science, Carnegie Mellon University Pittsburgh, PA 15213, USA som@ri.c Add to Reading List Source URL: somchaya.org Language: English - Date: 2014-05-05 11:44:38 Graph theory Mathematics Computational complexity theory Combinatorial optimization Matching Assignment problem Linear programming Multi-agent system Shortest path problem
82	Formula Mathematics Equation Mathematical Symbol Geometry Information Concept Add to Reading List Source URL: www.iscb.org Language: English - Date: 2016-04-19 12:52:08 Academia Bioinformatics Computational biology Biology Computational science Intelligent Systems for Molecular Biology International Society for Computational Biology Burkhard Rost Serafim Batzoglou Overton Prize Alfonso Valencia Alex Bateman
83	A Graph Expansion and Communication Costs of Fast Matrix Multiplication Grey Ballard, University of California at Berkeley James Demmel, University of California at Berkeley ¨ Berlin Add to Reading List Source URL: www.cs.huji.ac.il Language: English - Date: 2014-11-26 08:31:39 Mathematics Algebra Computational complexity theory Analysis of algorithms Multiplication Numerical linear algebra Matrix multiplication algorithm Matrix multiplication Strassen algorithm Fast Fourier transform Multiplication algorithm Algorithm
84	How to apply de Bruijn graphs to genome assembly Add to Reading List Source URL: www.nature.com Language: English - Date: 2012-01-20 11:24:28 Graph theory Mathematics Bioinformatics NP-complete problems Computational biology DNA sequencing K-mer Velvet assembler Eulerian path Hamiltonian path Degree Seven Bridges of Knigsberg
85	J Sci Educ Technol:127–147 DOIs10956Defining Computational Thinking for Mathematics and Science Classrooms David Weintrop1,2 • Elham Beheshti3 • Michael Horn1,2,3 • Kai Orton1,2 Add to Reading List Source URL: ccl.northwestern.edu Language: English - Date: 2016-05-03 12:24:06 Academia Engineering Knowledge Bioinformatics Formal sciences Computational thinking Computer science Neuroinformatics Complexity Mathematics Computational science Computational mathematics
86	ONE-ONE FUNCTIONS AND INVERSES MATH 152, SECTION 55 (VIPUL NAIK) Corresponding material in the book: Section 7.1. What students should definitely get: The definition of one-to-one function, the computational and checking Add to Reading List Source URL: files.vipulnaik.com Language: English - Date: 2016-08-13 11:33:29 Mathematical analysis Mathematics Analysis Functions and mappings Inverse function Function Convex function Injective function Continuous function Derivative Bijection Limit of a function
87	PDF Document Add to Reading List Source URL: mcqmc2016.stanford.edu Language: English - Date: 2016-08-23 18:37:55 Monte Carlo methods Statistics Applied mathematics Probability Quasirandomness Quasi-Monte Carlo method Computational physics Sampling techniques Statistical mechanics Markov chain Monte Carlo Monte Carlo Monte
88	ANNEX TO REPORT ON MATHEMATICS FOR EUROPE June 2016 The online consultation on mathematics was carried out from 29 January to 15 May 2016 by the European Commission Directorate General for Communications Networks, Conten Add to Reading List Source URL: www.math.cas.cz Language: English - Date: 2016-06-15 09:23:00 Academia Applied mathematics Computational science Computing Supercomputing Formal sciences Exascale computing Computational mathematics Mathematics Computer science Algorithm Mathematical optimization
89	Computational Thinking in the Science Classroom: Preliminary Findings from a Blended Curriculum David Weintrop, Kai Orton, Michael Horn, Elham Beheshti, Laura Trouille, Kemi Jona & Uri Wilensky Northwestern University Ab Add to Reading List Source URL: ccl.northwestern.edu Language: English - Date: 2016-05-03 12:24:06 Education Science and technology Science Engineering education Science education Education policy Mathematics education Computational thinking Science technology engineering and mathematics Association for Computing Machinery C-STEM Center
90	Norms of random submatrices and sparse approximation Joel A. Tropp 1 Applied & Computational Mathematics, California Institute of Technology, Pasadena, CAReceived ***; accepted after revision +++++ Present Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2008-07-28 20:32:09** Linear algebra Mathematics Matrix Norm

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