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Concentration of Measure for the Analysis of Randomized Algorithms

. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details;

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Concentration of Measure for the Analysis of Randomized Algorithms

. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details;

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Randomized Algorithms

For many applications a randomized algorithm is either the simplest algorithm available, or the fastest, or both. This tutorial presents;

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Positive 1d and 2D Systems

treatment explaining the genesis of randomized algorithms in the principles of probability theory to their use for robust analysis and controller;

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Theory Of Randomized Search Heuristics

optimization turn out to be highly successful for optimization in practice. The theory of randomized search heuristics, which has been growing rapidly;

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The Concentration of Measure Phenomenon

The observation of the concentration of measure phenomenon is inspired by isoperimetric inequalities. A familiar example is the way the;

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Randomized Routing Algorithms in Mobile Ad Hoc Networks

proposes several new randomized position-based algorithms for routing in mobile ad-hoc networks. The proposed algorithms incorporate two heuristics;

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Randomized Algorithms in Automatic Control and Data Mining

always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals;

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WALCOM: Algorithms and Computation

102 submissions. The papers feature original research in the areas of design and analysis of algorithms, computational geometry, graph drawing;

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Introduction To The Analysis Of Algorithms, An

This textbook covers the mathematical foundations of the analysis of algorithms. The gist of the book is how to argue, without the burden;

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Theory of Evolutionary Computation

search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics;

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Theory of Evolutionary Computation

search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics;

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Parallel Processing of Discrete Problems

optical models of computing, randomized parallel algorithms, general techniques for the design of parallel discrete algorithms, parallel;

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Mathematical Foundations for Data Analysis

Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds;

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Mathematical Foundations for Data Analysis

Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds;

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Random Processes For Engineers

the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward;

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Algorithms

Algorithms: Design and Analysis of is a textbook designed for the undergraduate and postgraduate students of computer science engineering;

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Computer Algorithms

, etc. They may also be classified as divide and conquer algorithm, search algorithm, randomized algorithm, etc. depending on the design;

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Nonlinear Biomedical Signal Processing, Volume 1

analysis methods to measure glucose concentration Nonlinear Biomedical Signal Processing, Volume I is a valuable reference tool for;

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The Pseudo Wigner Distribution for the Analysis of Doppler Ultrasound Signals

The time-frequency representations of the signals are a powerful tool for the analysis of non-stationary signals such as the biological;

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Introduction to Algorithms

as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and;

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Introduction To The Analysis Of Algorithms, An (3rd Edition)

A successor to the first and second editions, this updated and revised book is a leading companion guide for students and engineers alike;

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Bounds for Monotone Algorithms

for a certain scheduling problem. In a related matter, we classify monotone algorithms for the deterministic, randomized and online case and;

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Introduction to Distributed Algorithms

suitable for advanced undergraduate or graduate courses, whilst the coverage is sufficiently deep to make it useful for practising engineers and;

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A Guide to Experimental Algorithmics

methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions;

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Introduction To Algorithms 3rd

of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It;

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A Primer of Permutation Statistical Methods

. Permutation methods are optimal for small data sets and non-random samples, and are free of distributional assumptions. The book follows the;

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