Results 131 to 140 of about 277 (163)
Advances in Applied Mathematics, 1986 One can associate with an arbitrary algebroid formal group law F, defined over Fp, a sequence [n]F(x̄) (= [n − 1]F(x̄) ⊕Fx̄). These sequences for various F (multiplicative group, reduced elliptic curves and Abelian varieties) provide a variety of new ...
Chudnovsky, D.V, Chudnovsky, G.V
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Primality Testing and Integer Factorization in Public-Key Cryptography
Advances in Information Security, 2004Song Y Yan
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Clever Factorization Algorithms and Primality Testing
Springer Undergraduate Mathematics Series, 2018The main theoretical way of attacking RSA, at least when it is used with best practices, is by factoring the modulus. The most obvious way of factoring a number n is to try dividing by 2, 3, 5, 7, and so on, through all the primes less than \(\sqrt{n}\), until we find a factor.
Simon Rubinstein-Salzedo +1 more
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Integer Factorization and Primality Testing: A Randomized Approach
Alok Chauhan, Abhyuday Chauhanexaly +2 more sources
Applications: Algorithms, Primality and Factorization, Codes
2011This chapter describes some industrial applications of number theory, via computer science. We succinctly describe the main algorithms as well as their theoretical complexity or computation time. We use the notation O(f(n)) to denote a function ≤Cf(n); furthermore, the unimportant—at least from a theoretical point of view—constants which appear will be
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Parsimonious kernel extreme learning machine in primal via Cholesky factorization
Neural Networks, 2016Recently, extreme learning machine (ELM) has become a popular topic in machine learning community. By replacing the so-called ELM feature mappings with the nonlinear mappings induced by kernel functions, two kernel ELMs, i.e., P-KELM and D-KELM, are obtained from primal and dual perspectives, respectively.
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Sparse LSSVM in Primal Using Cholesky Factorization for Large-Scale Problems
IEEE Transactions on Neural Networks and Learning Systems, 2016For support vector machine (SVM) learning, least squares SVM (LSSVM), derived by duality LSSVM (D-LSSVM), is a widely used model, because it has an explicit solution. One obvious limitation of the model is that the solution lacks sparseness, which limits it from training large-scale problems efficiently.
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Primality tests and factorization algorithms. I
2001Schöne Übersichtsarbeit über Primzahltests; im vorliegenden Teil werden die theoretisch aufwendigeren Tests nach Adleman-Rumely-Pomerance-Cohen-Lenstra und Goldwasser-Kilian ausgespart. Für neueste Entwicklungen auf diesem Gebiet, vgl. ein Preprint von Agrawal, Kayal, Saxena (``PRIMES is in \(P\)''), wo ein deterministischer Polynomzeit-Algorithmus ...
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