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Bibliographies thématiques / Random combinatorial problems / Livres

Livres sur le sujet « Random combinatorial problems »

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Auteur : Grafiati

Publié le 14 mars 2023

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Consultez les 22 meilleurs livres pour votre recherche sur le sujet « Random combinatorial problems ».

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1

Yukich, Joseph. Probability theory of classical Euclidean optimization problems. Berlin : Springer, 1998.

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2

Chandra, Chekuri, et International Workshop on Randomization and Computation (9th : 2005 : Berkeley, Calif.), dir. Approximation, randomization, and combinatorial optimization : Algorithms and techniques : 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, and 9th International Workshop on Randomization and Computation, RANDOM 2005, Berkeley, CA, USA, August 22-24, 2005 : proceedings. Berlin : Springer, 2005.

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3

1950-, Díaz J., et International Workshop on Randomization and Computation (10th : 2006 : Barcelona, Spain), dir. Approximation, randomization and combinatorial optimization : Algorithms and techniques : 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006, and 10th International Workshop on Randomization and Computation, RANDOM 2006, Barcelona, Spain, August 28-30, 2006 : proceedings. Berlin : Springer, 2006.

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4

Spencer, Joel H. Asymptopia. Providence, Rhode Island : American Mathematical Society, 2014.

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5

International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (7th 2004 Cambridge, Mass.). Approximation, randomization, and combinatorial optimization : algorithms and techniques : 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2004, and 8th International Workshop on Randomization and Computation, RANDOM 2004, Cambridge, MA, USA, August 22-24, 2004 : proceedings. Berlin : Springer, 2004.

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6

International Workshop on Randomization and Approximation Techniques in Computer Science (3rd 1999 Berkeley, Calif.). Randomization, approximation, and combinatorial optimization : Algorithms and techniques : Third International Workshop on Randomization and Approximation Techniques in Computer Science, and Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems RANDOM-APPROX '99, Berkeley, CA, August 8-11, 1999, proceedings. Berlin : Springer, 1999.

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7

Sanjeev, Arora, et International Workshop on Randomization and Approximation Techniques in Computer Science (7th : 2003 : Princeton, N.J.), dir. Approximation, randomization, and combinatorial optimization : Algorithms and techniques : 6th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2003, and 7th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2003, Princeton, NJ, USA, August 24-26, 2003 : proceedings. Berlin : Springer, 2003.

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8

Michel, Goemans, et International Workshop on Randomization and Approximation Techniques in Computer Science (5th : 2001 : Berkeley, Calif.), dir. Approximation, randomization, and combinatorial optimization : Algorithms and techniques : 4th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2001 and 5th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2001, Berkeley, CA, USA, August 18-20, 2001, proceedings. New York : Springer, 2001.

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9

Paliy, Irina. Probability theory and mathematical statistics. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1065828.

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The tutorial is an introductory course in probability theory and mathematical statistics. Elements of combinatorics, basic concepts and theorems of probability theory, discrete random variables, continuous random variables, some limit theorems, one-dimensional and two-dimensional samples, point and interval estimation of parameters of the general population, testing of statistical hypotheses, elements of queuing theory are considered. The presentation of the theoretical material is accompanied by a large number of detailed examples of problem solving. For students of technical and economic fields of study and specialties, studying under the bachelor's and specialty programs.

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10

Paliy, Irina, V. A. Dalinger et B. S. Dobronec. Probability theory and mathematical statistics. ru : INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1859126.

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The textbook is an introductory course in probability theory and mathematical statistics. Elements of combinatorics, basic concepts and theorems of probability theory, discrete random variables, continuous random variables, some limit theorems, one-dimensional and two-dimensional samples, point and interval estimation of the parameters of the general population, verification of statistical hypotheses, elements of queuing theory are considered. The presentation of the theoretical material is accompanied by a large number of detailed examples of problem solving. For students of technical and economic areas of training and specialties, studying under bachelor's and specialty programs.

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11

Large networks and graph limits. Providence, Rhode Island : American Mathematical Society, 2012.

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12

Klaus, Jansen, Rolim José D. P, Servedio Rocco et SpringerLink (Online service), dir. Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques : 15th International Workshop, APPROX 2012, and 16th International Workshop, RANDOM 2012, Cambridge, MA, USA, August 15-17, 2012. Proceedings. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.

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13

Combinatorics and Random Matrix Theory. American Mathematical Society, 2016.

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14

Diaz, Josep, Klaus Jansen, José D. P. Rolim et Uri Zwick. Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques : 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 and 10th International Workshop on Randomization and Computation, RANDOM 2006, Barcelona, Spain, August 28-30, 2006, Proceedings. Springer London, Limited, 2006.

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15

Khanna, Sanjeev, Klaus Jansen, Dana Ron et José D. P. Rolim. Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques : 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2004 and 8th International Workshop on Randomization and Computation, RANDOM 2004, Cambridge, MA, USA August 22-24, 2004 , Proceedings. Springer London, Limited, 2004.

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16

Hochbaum, Dorit, Alistair Sinclair, Klaus Jansen et Jose D. P. Rolim. Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques : Third International Workshop on Randomization and Approximation Techniques in Computer Science, and Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems RANDOM-APPROX'99,Berkeley, CA, USA, August 8-11, 1999 Pro. Springer London, Limited, 2004.

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17

Arora, Sanjeev, Klaus Jansen, Amit Sahai et Jose D. P. Rolim. Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques : 6th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2003 and 7th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2003, Princeto, NY, USA, August 24-26,2003. Springer London, Limited, 2003.

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18

Trevisan, Luca, Klaus Jansen, José D. P. Rolim et Michel Goemans. Approximation, Randomization and Combinatorial Optimization : Algorithms and Techniques : 4th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2001 and 5th International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM 2001 Berkeley, CA,USA, August 18-20 2001. Springer London, Limited, 2003.

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19

Trevisan, Luca, Klaus Jansen, José D. P. Rolim et Chandra Chekuri. Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques : 8th International Workshop on Approximation Algorithms for Compinatorial Optimization Problems, APPROX 2005 and 9th International Workshop on Randomization and Computation, RANDOM 2005, Berkeley, CA, USA, August 22-24, 2005, Proceedings. Springer London, Limited, 2005.

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20

Fayolle, Guy, Roudolf Iasnogorodski et Vadim Malyshev. Random Walks in the Quarter Plane : Algebraic Methods, Boundary Value Problems, Applications to Queueing Systems and Analytic Combinatorics. Springer, 2017.

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21

Fayolle, Guy, Roudolf Iasnogorodski et Vadim Malyshev. Random Walks in the Quarter Plane : Algebraic Methods, Boundary Value Problems, Applications to Queueing Systems and Analytic Combinatorics. Springer, 2018.

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22

Marks II, Robert J. Handbook of Fourier Analysis & ; Its Applications. Oxford University Press, 2009. http://dx.doi.org/10.1093/oso/9780195335927.001.0001.

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Fourier analysis has many scientific applications - in physics, number theory, combinatorics, signal processing, probability theory, statistics, option pricing, cryptography, acoustics, oceanography, optics and diffraction, geometry, and other areas. In signal processing and related fields, Fourier analysis is typically thought of as decomposing a signal into its component frequencies and their amplitudes. This practical, applications-based professional handbook comprehensively covers the theory and applications of Fourier Analysis, spanning topics from engineering mathematics, signal processing and related multidimensional transform theory, and quantum physics to elementary deterministic finance and even the foundations of western music theory. As a definitive text on Fourier Analysis, Handbook of Fourier Analysis and Its Applications is meant to replace several less comprehensive volumes on the subject, such as Processing of Multifimensional Signals by Alexandre Smirnov, Modern Sampling Theory by John J. Benedetto and Paulo J.S.G. Ferreira, Vector Space Projections by Henry Stark and Yongyi Yang and Fourier Analysis and Imaging by Ronald N. Bracewell. In addition to being primarily used as a professional handbook, it includes sample problems and their solutions at the end of each section and thus serves as a textbook for advanced undergraduate students and beginning graduate students in courses such as: Multidimensional Signals and Systems, Signal Analysis, Introduction to Shannon Sampling and Interpolation Theory, Random Variables and Stochastic Processes, and Signals and Linear Systems.

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