Results 181 to 190 of about 65,804 (214)
Some of the next articles are maybe not open access.
Oberwolfach Reports, 2015
The p-Laplacian operators have a rich analytical theory and in the last few years they have also offered efficient tools to tackle several tasks in machine learning. During the workshop mathematicians and theoretical computer scientists working on models
Matthias Hein, D. Lenz, Delio Mugnolo
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The p-Laplacian operators have a rich analytical theory and in the last few years they have also offered efficient tools to tackle several tasks in machine learning. During the workshop mathematicians and theoretical computer scientists working on models
Matthias Hein, D. Lenz, Delio Mugnolo
semanticscholar +1 more source
Discrete Mathematical Structures in Computer Science
2015Η εξέλιξη της επιστήμης των υπολογιστών στηρίζεται στην έρευνα για την ανάπτυξη υλισμικού, όσο και σε εκείνη που αφορά το λογισμικό (software). Ακρογωνιαίος λίθος στην στήριξη της έρευνας και στις δυο αυτές περιοχές είναι τα διακριτά μαθηματικά. Ειδικότερα, οι περιοχές της μαθηματικής λογικής, της συνδυαστικής, της θεωρίας των γράφων, της γραμμικής ...
Georgiou, Dimitrios +2 more
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Technical Symposium on Computer Science Education
Discrete mathematics has been a topic taught in the undergraduate computer science curriculum for decades. Most research publications that are focused on discrete mathematics focus on the teacher's perspective of the course and the students.
David Magda, Christina Gardner-Mccune
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Discrete mathematics has been a topic taught in the undergraduate computer science curriculum for decades. Most research publications that are focused on discrete mathematics focus on the teacher's perspective of the course and the students.
David Magda, Christina Gardner-Mccune
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Connecting Discrete Mathematics and Computer Science
2022Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to learn this?' Written with these students in mind, this text introduces the mathematical foundations of computer science by providing a comprehensive treatment of standard technical topics while simultaneously illustrating some of the ...
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PROBLEMS OF TEACHING ELEMENTS OF DISCRETE MATHEMATICS TO FUTURE COMPUTER SCIENCE TEACHERS
BULLETIN Series of Physics & Mathematical Sciences, 2021The article deals with the problem of integrated teaching of discrete mathematics elements to the content of the main specialized disciplines in the preparation of future computer science teachers. The ways of solving some problems in the preparation of future computer science teachers on the elements of discrete mathematics and the need for its ...
B.G. Bostanov, Z.T. Suranchiyeva
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Applied Discrete Mathematics, Combinatorics, Cryptography, Computer Science and Computation
Journal of Discrete Mathematical Sciences and CryptographyThis special issue of “Applied Discrete Mathematics, Combinatorics, Cryptography, Computer Science and Computation”, presents a selection of cutting-edge research in the fields of cryptography, algebra, and module theory. These areas continue to evolve and provide foundational insights for modern technology, particularly in the realms of secure ...
Mohammad Reza Farahani +4 more
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Review of Essential Discrete Mathematics for Computer Science By Harry Lewis and Rachel Zax
ACM SIGACT News, 2020In this column we state a class of open problems that are well known in Ramsey Theory but probably not to my non-Ramsey readers. Nothing I present is original.
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Discrete mathematics, computer science, logic, proof, and their relationships
2021Discrete mathematics, roughly defined as concerning countable objects, recently gained importance both in research and education, mainly due to its foundational role in large parts of computer science. This chapter provides a synthesis of recent INDRUM research concerning the educational side of this “border area” between university mathematics and ...
Chellougui, Faïza +2 more
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Research Area 3: Mathematical Sciences: 3.4, Discrete Mathematics and Computer Science
2015Abstract : Many modern applications require modeling and analysis of functions on large, high dimensional, unstructured data sets. One may assume that the data lies on a low dimensional manifold, but this manifold is not known. We have extended the diffusion geometry paradigm for these problems to study function approximation on data defined manifolds.
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