Literatura académica sobre el tema "Algorithms"
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Artículos de revistas sobre el tema "Algorithms"
Sun, Yuqin, Songlei Wang, Dongmei Huang, Yuan Sun, Anduo Hu y Jinzhong Sun. "A multiple hierarchical clustering ensemble algorithm to recognize clusters arbitrarily shaped". Intelligent Data Analysis 26, n.º 5 (5 de septiembre de 2022): 1211–28. http://dx.doi.org/10.3233/ida-216112.
Texto completoGościniak, Ireneusz y Krzysztof Gdawiec. "Visual Analysis of Dynamics Behaviour of an Iterative Method Depending on Selected Parameters and Modifications". Entropy 22, n.º 7 (2 de julio de 2020): 734. http://dx.doi.org/10.3390/e22070734.
Texto completoGangavane, Ms H. N. "A Comparison of ABK-Means Algorithm with Traditional Algorithms". International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (30 de junio de 2017): 614–21. http://dx.doi.org/10.31142/ijtsrd2197.
Texto completoNico, Nico, Novrido Charibaldi y Yuli Fauziah. "Comparison of Memetic Algorithm and Genetic Algorithm on Nurse Picket Scheduling at Public Health Center". International Journal of Artificial Intelligence & Robotics (IJAIR) 4, n.º 1 (30 de mayo de 2022): 9–23. http://dx.doi.org/10.25139/ijair.v4i1.4323.
Texto completoOmar, Hoger K., Kamal H. Jihad y Shalau F. Hussein. "Comparative analysis of the essential CPU scheduling algorithms". Bulletin of Electrical Engineering and Informatics 10, n.º 5 (1 de octubre de 2021): 2742–50. http://dx.doi.org/10.11591/eei.v10i5.2812.
Texto completoHairol Anuar, Siti Haryanti, Zuraida Abal Abas, Norhazwani Mohd Yunos, Nurul Hafizah Mohd Zaki, Nurul Akmal Hashim, Mohd Fariddudin Mokhtar, Siti Azirah Asmai, Zaheera Zainal Abidin y Ahmad Fadzli Nizam. "Comparison between Louvain and Leiden Algorithm for Network Structure: A Review". Journal of Physics: Conference Series 2129, n.º 1 (1 de diciembre de 2021): 012028. http://dx.doi.org/10.1088/1742-6596/2129/1/012028.
Texto completoAgapie, Alexandru. "Theoretical Analysis of Mutation-Adaptive Evolutionary Algorithms". Evolutionary Computation 9, n.º 2 (junio de 2001): 127–46. http://dx.doi.org/10.1162/106365601750190370.
Texto completoBelazi, Akram, Héctor Migallón, Daniel Gónzalez-Sánchez, Jorge Gónzalez-García, Antonio Jimeno-Morenilla y José-Luis Sánchez-Romero. "Enhanced Parallel Sine Cosine Algorithm for Constrained and Unconstrained Optimization". Mathematics 10, n.º 7 (3 de abril de 2022): 1166. http://dx.doi.org/10.3390/math10071166.
Texto completoLuan, Yuxuan, Junjiang He, Jingmin Yang, Xiaolong Lan y Geying Yang. "Uniformity-Comprehensive Multiobjective Optimization Evolutionary Algorithm Based on Machine Learning". International Journal of Intelligent Systems 2023 (10 de noviembre de 2023): 1–21. http://dx.doi.org/10.1155/2023/1666735.
Texto completoSHAH, I. "DIRECT ALGORITHMS FOR FINDING MINIMAL UNSATISFIABLE SUBSETS IN OVER-CONSTRAINED CSPs". International Journal on Artificial Intelligence Tools 20, n.º 01 (febrero de 2011): 53–91. http://dx.doi.org/10.1142/s0218213011000036.
Texto completoTesis sobre el tema "Algorithms"
Yarmolskyy, Oleksandr. "Využití distribuovaných a stochastických algoritmů v síti". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-370918.
Texto completoCrocomo, Márcio Kassouf. "Algoritmo de otimização bayesiano com detecção de comunidades". Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-23012013-160605/.
Texto completoESTIMATION of Distribution Algorithms represent a research area which is showing promising results, especially in dealing with complex large scale problems. In this context, the Bayesian Optimization Algorithm (BOA) uses a multivariate model (represented by a Bayesian network) to find new solutions at each iteration. Based on BOA and in the study of community detection algorithms (to improve the constructed multivariate models), two new algorithms are proposed, named CD-BOA and StrOp. This paper indicates that both algorithms have significant advantages when compared to BOA. The CD-BOA is shown to be more flexible, being more robust when using different input parameters, what makes it easier to deal with a greater diversity of real-world problems. Unlike CD-BOA and BOA, StrOp shows that the detection of communities on a Bayesian network more adequately models decomposable problems, resulting in simpler subproblems that can be solved by a greedy search, resulting in a solution to the original problem which may be optimal in the case of perfectly decomposable problems, or a fair approximation if not. Another proposal is a new resampling technique for EDAs (called REDA). This technique results in multivariate models that are more representative, significantly improving the performance of CD-BOA and StrOp. In general, it is shown that, for the scenarios tested, CD-BOA and StrOp require lower running time than BOA. This indication is done experimentally and by the analysis of the computational complexity of the algorithms. The main features of these algorithms are evaluated for solving various problems, thus identifying their contributions to the field of Evolutionary Computation
Davidsdottir, Agnes. "Algorithms, Turing machines and algorithmic undecidability". Thesis, Uppsala universitet, Algebra och geometri, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-441282.
Texto completoTikhonenko, Dmitrii. "Managing algorithmic drivers in a blocked-lane scenario". Doctoral thesis, Universitat Pompeu Fabra, 2020. http://hdl.handle.net/10803/670829.
Texto completoEn aquesta tesi, es discuteixen diferents aspectes de la gestió els conductors assistits per algoritmes en un escenari de carril bloquejat. El primer capítol presenta un algorisme de la gestió òptima dels conductors egoistes. La política òptima pot incloure oscil.lacions de velocitat no desitjades. Proposem mesures per a un planificador central per erradicar-les i comprovem l’eficiència del nostre algoritme enfront de les polítiques heurístiques populars. En el segon capítol, es desenvolupa un mecanisme per a la licitació posicional dels conductors. Permet negociar posicions per carretera dels conductors amb valoracions de temps heterogènies, donant lloc a un resultat socialment beneficiós. El capítol final presenta una política d’aprenentatge profund per a l’aclariment centralitzat del coll d’ampolla en el menor temps possible. El seu ús és prou ràpid per permetre futures aplicacions operatives, i un conjunt de formació consisteix en polítiques de fusió `òptimes a nivell mundial.
Sauerland, Volkmar [Verfasser]. "Algorithm Engineering for some Complex Practise Problems : Exact Algorithms, Heuristics and Hybrid Evolutionary Algorithms / Volkmar Sauerland". Kiel : Universitätsbibliothek Kiel, 2012. http://d-nb.info/1026442745/34.
Texto completoAguiar, Marilton Sanchotene de. "Análise formal da complexidade de algoritmos genéticos". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1998. http://hdl.handle.net/10183/25941.
Texto completoThe objective of the work is to study the viability of treating optimization problems, considered intractable, through Genetic Algorithms, developing approaches for the qualitative evaluation of a Genetic Algorithm. Inside this theme, approached areas: complexity, classes of problems, analysis and development of algorithms and Genetic Algorithms, this last one being central object of the study. As product of the study of this theme, a development method of Genetic Algorithms is proposed, using the whole formal study of types of problems, development of approximate algorithms and complexity analysis. The fact that a problem theoretically solvable isn’t enough to mean that it is solvable in pratice. A problem is denominated easy if in the worst case it possesses an algorithm reasonably efficient. And an algorithm is said reasonably efficient when a polynomial p exists such that for any entrance size n the algorithm terminates at maximum of p(n) steps [SZW 84]. Since a polynomial can be of very high order, then an algorithm of polynomial complexity can be very inefficient. The premise of the Genetic Algorithms is that one can find approximate solutions of problems of great computational complexity by means of a process of simulated evolution [LAG 96]. As product of the study of this theme, a method of development of Genetic Algorithms with the quality conscience is proposed, using the whole formal study of types of problems, development of approximate algorithms and complexity analysis. The axiom set has the purpose of giving the semantics of the algorithm, in other words, it defines formally the operation of the algorithm, more specifically of the functions and procedures of the algorithm. And this, facilitates the planner of algorithms a larger safety in the development, because in order to prove the correction of a Genetic Algorithm that satisfies that model it is only necessary to prove that the procedures satisfy the axioms. To have conscience of the quality of an approximate algorithm, two factors are important: the accuracy and the complexity. This work lifts the important points for the study of the complexity of a Genetic Algorithm. Unhappily, they are conflicting factors, because as larger the accuracy, worse (higher) it is the complexity, and vice-versa. Thus, a study of the quality of a Genetic Algorithm, considered an approximate algorithm, would be only complete with the consideration of these two factors. But, this work provides a great step in direction of the study of the viability of the treatment of optimization problems through Genetic Algorithms.
Stults, Ian Collier. "A multi-fidelity analysis selection method using a constrained discrete optimization formulation". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31706.
Texto completoCommittee Chair: Mavris, Dimitri; Committee Member: Beeson, Don; Committee Member: Duncan, Scott; Committee Member: German, Brian; Committee Member: Kumar, Viren. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Violich, Stephen Scott. "Fusing Loopless Algorithms for Combinatorial Generation". Thesis, University of Canterbury. Computer Science and Software Engineering, 2006. http://hdl.handle.net/10092/1075.
Texto completoLi, Quan Ph D. Massachusetts Institute of Technology. "Algorithms and algorithmic obstacles for probabilistic combinatorial structures". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115765.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 209-214).
We study efficient average-case (approximation) algorithms for combinatorial optimization problems, as well as explore the algorithmic obstacles for a variety of discrete optimization problems arising in the theory of random graphs, statistics and machine learning. In particular, we consider the average-case optimization for three NP-hard combinatorial optimization problems: Large Submatrix Selection, Maximum Cut (Max-Cut) of a graph and Matrix Completion. The Large Submatrix Selection problem is to find a k x k submatrix of an n x n matrix with i.i.d. standard Gaussian entries, which has the largest average entry. It was shown in [13] using non-constructive methods that the largest average value of a k x k submatrix is 2(1 + o(1) [square root] log n/k with high probability (w.h.p.) when k = O(log n/ log log n). We show that a natural greedy algorithm called Largest Average Submatrix LAS produces a submatrix with average value (1+ o(1)) [square root] 2 log n/k w.h.p. when k is constant and n grows, namely approximately [square root] 2 smaller. Then by drawing an analogy with the problem of finding cliques in random graphs, we propose a simple greedy algorithm which produces a k x k matrix with asymptotically the same average value (1+o(1) [square root] 2log n/k w.h.p., for k = o(log n). Since the maximum clique problem is a special case of the largest submatrix problem and the greedy algorithm is the best known algorithm for finding cliques in random graphs, it is tempting to believe that beating the factor [square root] 2 performance gap suffered by both algorithms might be very challenging. Surprisingly, we show the existence of a very simple algorithm which produces a k x k matrix with average value (1 + o[subscript]k(1) + o(1))(4/3) [square root] 2log n/k for k = o((log n)¹.⁵), that is, with asymptotic factor 4/3 when k grows. To get an insight into the algorithmic hardness of this problem, and motivated by methods originating in the theory of spin glasses, we conduct the so-called expected overlap analysis of matrices with average value asymptotically (1 + o(1))[alpha][square root] 2 log n/k for a fixed value [alpha] [epsilon] [1, fixed value a E [1, [square root]2]. The overlap corresponds to the number of common rows and common columns for pairs of matrices achieving this value. We discover numerically an intriguing phase transition at [alpha]* [delta]= 5[square root]2/(3[square root]3) ~~ 1.3608.. [epsilon] [4/3, [square root]2]: when [alpha] < [alpha]* the space of overlaps is a continuous subset of [0, 1]², whereas [alpha] = [alpha]* marks the onset of discontinuity, and as a result the model exhibits the Overlap Gap Property (OGP) when [alpha] > [alpha]*, appropriately defined. We conjecture that OGP observed for [alpha] > [alpha]* also marks the onset of the algorithmic hardness - no polynomial time algorithm exists for finding matrices with average value at least (1+o(1)[alpha][square root]2log n/k, when [alpha] > [alpha]* and k is a growing function of n. Finding a maximum cut of a graph is a well-known canonical NP-hard problem. We consider the problem of estimating the size of a maximum cut in a random Erdős-Rényi graph on n nodes and [cn] edges. We establish that the size of the maximum cut normalized by the number of nodes belongs to the interval [c/2 + 0.47523[square root]c,c/2 + 0.55909[square root]c] w.h.p. as n increases, for all sufficiently large c. We observe that every maximum size cut satisfies a certain local optimality property, and we compute the expected number of cuts with a given value satisfying this local optimality property. Estimating this expectation amounts to solving a rather involved multi-dimensional large deviations problem. We solve this underlying large deviation problem asymptotically as c increases and use it to obtain an improved upper bound on the Max-Cut value. The lower bound is obtained by application of the second moment method, coupled with the same local optimality constraint, and is shown to work up to the stated lower bound value c/2 + 0.47523[square root]c. We also obtain an improved lower bound of 1.36000n on the Max-Cut for the random cubic graph or any cubic graph with large girth, improving the previous best bound of 1.33773n. Matrix Completion is the problem of reconstructing a rank-k n x n matrix M from a sampling of its entries. We propose a new matrix completion algorithm using a novel sampling scheme based on a union of independent sparse random regular bipartite graphs. We show that under a certain incoherence assumption on M and for the case when both the rank and the condition number of M are bounded, w.h.p. our algorithm recovers an [epsilon]-approximation of M in terms of the Frobenius norm using O(nlog² (1/[epsilon])) samples and in linear time O(nlog² (1/[epsilon])). This provides the best known bounds both on the sample complexity and computational cost for reconstructing (approximately) an unknown low-rank matrix. The novelty of our algorithm is two new steps of thresholding singular values and rescaling singular vectors in the application of the "vanilla" alternating minimization algorithm. The structure of sparse random regular graphs is used heavily for controlling the impact of these regularization steps.
by Quan Li.
Ph. D.
Astete, morales Sandra. "Contributions to Convergence Analysis of Noisy Optimization Algorithms". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS327/document.
Texto completoThis thesis exposes contributions to the analysis of algorithms for noisy functions. It exposes convergence rates for linesearch algorithms as well as for random search algorithms. We prove in terms of Simple Regret and Cumulative Regret that a Hessian based algorithm can reach the same results as some optimal algorithms in the literature, when parameters are tuned correctly. On the other hand we analyse the convergence order of Evolution Strategies when solving noisy functions. We deduce log-log convergence. We also give a lower bound for the convergence rate of the Evolution Strategies. We extend the work on revaluation by applying it to a discrete settings. Finally we analyse the performance measure itself and prove that the use of an erroneus performance measure can lead to misleading results on the evaluation of different methods
Libros sobre el tema "Algorithms"
Smith, Jeffrey Dean. Design and analysis of algorithms. Boston: PWS-KENT Pub. Co., 1989.
Buscar texto completoDesigning efficient algorithms for parallel computers. New York: McGraw-Hill, 1987.
Buscar texto completoDesigning efficient algorithms for parallel computers. Maidenhead: McGraw, 1988.
Buscar texto completoChang, Lin, William D. Chey, John Kellow, Jan Tack y William E. Whitehead, eds. Rome IV Diagnostic Algorithms. Raleigh, NC USA: The Rome Foundation, 2016. http://dx.doi.org/10.24890/algorithms.
Texto completoGriffiths, P. 1947 Oct. 29- y Hill I. D. 1926-, eds. Applied statistics algorithms. Chichester: Published by E. Horwood for the Royal Statistical Society, London, 1985.
Buscar texto completoRapanotti, L. Algorithm engineering for integral and dynamic problems. Amsterdam: Gordon & Breach, 2001.
Buscar texto completoBaase, Sara. Computer algorithms: Introduction to design and analysis. 2a ed. Reading, Mass: Addison-Wesley Pub. Co., 1991.
Buscar texto completoBaase, Sara. Computer algorithms: Introduction to design and analysis. 2a ed. Reading, Mass: Addison-Wesley Pub. Co., 1988.
Buscar texto completoVerfasserIn, Van Gelder Allen, ed. Computer algorithms: Introduction to design and analysis. 3a ed. Delhi: Pearson Education, 2009.
Buscar texto completoEbers, Martin y Marta Cantero Gamito, eds. Algorithmic Governance and Governance of Algorithms. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50559-2.
Texto completoCapítulos de libros sobre el tema "Algorithms"
Taillard, Éric D. "Elements of Graphs and Complexity Theory". En Design of Heuristic Algorithms for Hard Optimization, 3–29. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13714-3_1.
Texto completoLalov, Boyan. "Algorithms Creating Algorithms". En Artificial Neural Networks – ICANN 2010, 303–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15825-4_39.
Texto completoLeiserson, Charles E. "Algorithmic analysis of multithreaded algorithms". En Algorithms and Computation, 132. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63890-3_15.
Texto completoBez, Helmut y Tony Croft. "Quantum algorithms 2: Simon's algorithm". En Quantum Computation, 333–42. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003264569-23.
Texto completoGalil, Zvi. "Recent progress in string algorithms". En Algorithms, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_49.
Texto completoPippenger, Nicholas. "Selection networks". En Algorithms, 2–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_50.
Texto completoNagamochi, Hiroshi y Toshihide Ibaraki. "Computing edge-connectivity in multiple and capacitated graphs". En Algorithms, 12–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_51.
Texto completoImai, Hiroshi y Kazuo Iwano. "Efficient sequential and parallel algorithms for planar minimum cost flow". En Algorithms, 21–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_52.
Texto completoWatanabe, Osamu y Seinosuke Toda. "Structural analyses on the complexity of inverting functions". En Algorithms, 31–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_53.
Texto completoAllender, Eric. "Oracles versus proof techniques that do not relativize". En Algorithms, 39–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_54.
Texto completoActas de conferencias sobre el tema "Algorithms"
Sambasivan, Lokesh Kumar, Joydeb Mukherjee y Dinkar Mylaraswamy. "Benchmarking Diagnostic Algorithms". En ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-28194.
Texto completoPerju, Veaceslav y Dorian Saranciuc. "Evaluation of the Multi-Algorithms Targets Recognition Systems". En 12th International Conference on Electronics, Communications and Computing. Technical University of Moldova, 2022. http://dx.doi.org/10.52326/ic-ecco.2022/cs.05.
Texto completoMcCormick, N. J. y Z. Tao. "Algorithms for bioluminescence estimation". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.thff3.
Texto completoBadi, Manjulata, Sheila Mahapatra y Saurav Raj. "A SOLUTION OF RPM FOR ACTIVE AND REACTIVE LOADING COMPENSATION". En TOPICS IN INTELLIGENT COMPUTING AND INDUSTRY DESIGN (ICID). Volkson Press, 2022. http://dx.doi.org/10.26480/icpesd.02.2022.135.140.
Texto completoShowalter, Mark, Dennis Hong y Daniel Larimer. "Development and Comparison of Gait Generation Algorithms for Hexapedal Robots Based on Kinematics With Considerations for Workspace". En ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49616.
Texto completoJesus, Alexandre D., Arnaud Liefooghe, Bilel Derbel y Luís Paquete. "Algorithm selection of anytime algorithms". En GECCO '20: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3377930.3390185.
Texto completoMaiti, Arnab y Palash Dey. "Parameterized Algorithms for Kidney Exchange". En Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/58.
Texto completoBulavintsev, Vadim y Dmitry Zhdanov. "Method for Adaptation of Algorithms to GPU Architecture". En 31th International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/graphicon-2021-3027-930-941.
Texto completoSun, Tao, Dongsheng Li, Zhe Quan, Hao Jiang, Shengguo Li y Yong Dou. "Heavy-ball Algorithms Always Escape Saddle Points". En Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/488.
Texto completoGhosh, Anjan y Paparao Palacharla. "Efficient optical preprocessing using split-step algorithms". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.tudd2.
Texto completoInformes sobre el tema "Algorithms"
Marty, Frédéric y Thierry Warin. Deciphering Algorithmic Collusion: Insights from Bandit Algorithms and Implications for Antitrust Enforcement. CIRANO, diciembre de 2023. http://dx.doi.org/10.54932/iwpg7510.
Texto completoTipton, Kelley, Brian F. Leas, Emilia Flores, Christopher Jepson, Jaya Aysola, Jordana Cohen, Michael Harhay et al. Impact of Healthcare Algorithms on Racial and Ethnic Disparities in Health and Healthcare. Agency for Healthcare Research and Quality (AHRQ), diciembre de 2023. http://dx.doi.org/10.23970/ahrqepccer268.
Texto completoJohansen, Richard A., Christina L. Saltus, Molly K. Reif y Kaytee L. Pokrzywinski. A Review of Empirical Algorithms for the Detection and Quantification of Harmful Algal Blooms Using Satellite-Borne Remote Sensing. U.S. Army Engineer Research and Development Center, junio de 2022. http://dx.doi.org/10.21079/11681/44523.
Texto completoBaader, Franz y Rafael Peñaloza. Axiom Pinpointing in General Tableaux. Aachen University of Technology, 2007. http://dx.doi.org/10.25368/2022.159.
Texto completoBaader, Franz y Rafael Peñaloza. Pinpointing in Terminating Forest Tableaux. Technische Universität Dresden, 2008. http://dx.doi.org/10.25368/2022.166.
Texto completoArthur, Jennifer Ann. Genetic Algorithms. Office of Scientific and Technical Information (OSTI), agosto de 2017. http://dx.doi.org/10.2172/1375151.
Texto completoSahni, Sartaj. Parallel Algorithms. Fort Belvoir, VA: Defense Technical Information Center, junio de 1999. http://dx.doi.org/10.21236/ada369856.
Texto completoVazirani, Umesh. Quantum Algorithms. Fort Belvoir, VA: Defense Technical Information Center, enero de 2013. http://dx.doi.org/10.21236/ada579025.
Texto completoHousley, R. Guidelines for Cryptographic Algorithm Agility and Selecting Mandatory-to-Implement Algorithms. RFC Editor, noviembre de 2015. http://dx.doi.org/10.17487/rfc7696.
Texto completoCordeiro de Amorim, Renato. A survey on feature weighting based K-Means algorithms. Web of Open Science, diciembre de 2020. http://dx.doi.org/10.37686/ser.v1i2.79.
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