portada Concentration of Measure for the Analysis of Randomized Algorithms (en Inglés)

Concentration of Measure for the Analysis of Randomized Algorithms (en Inglés)

Formato

Libro Físico

Autor

Devdatt P. Dubhashi

Alessandro Panconesi

Editorial

Cambridge University Press

Año

2012

Idioma

Inglés

N° páginas

212

Encuadernación

Tapa Blanda

Dimensiones

22.6x15x1.5 cm

Peso

0.34 kg.

ISBN

1107606608

ISBN13

9781107606609

N° edición

Categorías

Algoritmos y estructuras de datos

Concentration of Measure for the Analysis of Randomized Algorithms (en Inglés)

Devdatt P. Dubhashi (Autor) · Alessandro Panconesi (Autor) · Cambridge University Press · Tapa Blanda

Libro Nuevo Importado

Envío: 16 a 22 días háb.

$ 147.30$ 73.65

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 50 unidades

$ 73.65

Llega entre el 15 Sep y el 25 Sep a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Concentration of Measure for the Analysis of Randomized Algorithms (en Inglés)"

Randomized algorithms have become a central part of the algorithms curriculum based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high- probability estimates on the performance of randomized algorithms. It covers the basic tool kit from the Chernoff-Hoeffding (CH) bounds to more sophisticated techniques like Martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities, and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as CH bounds in dependent settings. The authors emphasize comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians.