الصفحة 82
الصفحة 82
All of Nonparametric Statistics
The goal of this text is to provide the reader with a single book where they can find a brief account of many, modern topics in nonparametric inference. The book is aimed at Master's level or Ph.D. level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods.This text covers a wide range of topics including: the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book has a mixture of methods and theory.
Algoritmi : Lo spirito dell’informatica = Algorithms : The spirit of information technology
Algorithms are the heart of computer science and mathematics, since without them the use of computers would not be possible. In this book, which in its English edition has been a longtime bestseller, Harel and Feldmann answer all questions relating to this topic. They talk about the evaluation, correctness and effectiveness of algorithms, but also clarify some doubts about programming techniques and also refer to the very current discussion on quantum computing. The book is useful both as a basic text for an introductory university course in computer science, and as a general introduction to natural sciences, mathematics or engineering.
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Real Algebraic Geometry
The algorithmic problems of real algebraic geometry such as real root counting, deciding the existence of solutions of systems of polynomial equations and inequalities, finding global maxima or deciding whether two points belong in the same connected component of a semi-algebraic set appear frequently in many areas of science and engineering. In this first-ever graduate textbook on the algorithmic aspects of real algebraic geometry, the main ideas and techniques presented form a coherent and rich body of knowledge, linked to many areas of mathematics and computing.
Algorithms in Invariant Theory
The book of Sturmfels is both an easy-to-read textbook for invariant theory and a challenging research monograph that introduces a new approach to the algorithmic side of invariant theory. The Groebner bases method is the main tool by which the central problems in invariant theory become amenable to algorithmic solutions.
Algorithms in Bioinformatics ; Vol.4175 : 6th International Workshop, WABI 2006, Zurich, Switzerland, September 11-13, 2006, Proceedings
This book constitutes the refereed proceedings of the 6th International Workshop on Algorithms in Bioinformatics, WABI 2006, held in Zurich, Switzerland in September 2006 in the course of the ALGO 2006 conference meetings. The 36 revised full papers presented were carefully reviewed and selected from 100 submissions. All current issues of algorithms in bioinformatics are addressed, ranging from mathematical tools to experimental studies of approximation algorithms and reports on significant computational analyses. Numerous biological problems are dealt with, including genetic mapping, sequence alignment and sequence analysis, phylogeny, comparative genomics, and protein structure. For the first time also machine-learning approaches along with combinatorial optimization are covered.
Algorithms in Bioinformatics ; Vol. 3692 ; 5th international workshop, WABI 2005, Mallorca, Spain, October 3-6, 2005, Proceedings
this book present the proceedings of the 5th Workshop on Algorithmsin Bioinformatics (WABI 2005) which took place in Spain, 2005. The Workshop on Algorithms in Bioinformatics highlights research workspecifically developed to address algorithmic problems in biosequence analysis. The emphasis is therefore on statistical and probabilistic algorithms that addressimportant problems in the field of molecular and structural biology. the workshop aims to present recent research results, includingsignificant work in progress, and to identify and explore directions of futureresearch.Original research papers (including significant work in progress) or state-of-the-art surveys were solicited on all aspects of algorithms in bioinformatics,including, but not limited to: exact and approximate algorithms for genomics,genetics, sequence analysis, gene and signal recognition, alignment, molecularevolution, phylogenetics, structure determination or prediction, gene expressionand gene networks, proteomics, functional genomics, and drug design.
Algorithms in Bioinformatics ; 8th International Workshop, WABI 2008, Karlsruhe, Germany, September 15-19, 2008. Proceedings
This book constitutes the refereed proceedings of the 8th International Workshop on Algorithms in Bioinformatics, WABI 2008, held in Karlsruhe, Germany, in September 2008 as part of the ALGO 2008 meeting.
Algorithms in Bioinformatics ; 7th International Workshop, WABI 2007, Philadelphia, PA, USA, September 8-9, 2007, Proceedings
All current issues of algorithms in bioinformatics are addressed, ranging from mathematical tools to experimental studies of approximation algorithms and reports on significant computational analyses. Numerous biological problems are dealt with, including genetic mapping, sequence alignment and sequence analysis, phylogeny, comparative genomics, and protein structure. Furthermore the papers feature high-performance computing approaches to computationally hard learning and optimization problems in bioinformatics and cover methods, software and dataset repositories for development and testing of such algorithms and their underlying models.
Algorithms for Fuzzy Clustering : Methods in c-Means Clustering with Applications
The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. We emphasize in this book is a family of algorithms using entropy or entropy-regularized methods which are less known, but we consider the entropy-based method to be another useful method of fuzzy c-means.
Algorithms for Decision Making
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.
Algorithms for Approximation ; Proceedings of the 5th International Conference, Chester, July 2005
Approximation methods are vital in many challenging applications of computational science and engineering. This is a collection of papers from world experts in a broad variety of relevant applications.
Algorithms for a New World : When Big Data and Mathematical Models Meet
Algorithms, artificial neural networks, and machine learning help us discover the opportunities and pitfalls of a world governed by mathematics and artificial intelligence.
Algorithms and Programming : Problems and Solutions
This book containing classical and well-known problems supplemented by clear and in-depth explanations. The material covered includes such topics as combinatorics, sorting, searching, queues, grammar and parsing, selected well-known algorithms and much more.
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithms and data structures ; 9th international workshop, WADS 2005, Waterloo, Canada, August 15-17, 2005, Proceedings
The papers in this volume were presented at the 9th Workshop on Algorithmsand Data Structures (WADS 2005). at the University of Waterloo, Waterloo, Canada. The workshopalternates with the Scandinavian Workshop on Algorithm Theory (SWAT), con-tinuing the tradition of SWAT and WADS starting with SWAT 1988 and WADS1989. From 90 submissions, the Program Committee selected 37 papers for pre-sentation at the workshop. includ Algorithm Analysis and Problem Complexity Data Structures Discrete Mathematics in Computer Science Computer Graphics Numeric Computing
Algorithms and data structures : The Basic Toolbox
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language.
Algorithms and computation ; 19th International symposium, ISAAC 2008, Gold Coast, Australia, December 15-17, 2008. Proceedings
This book constitutes the refereed proceedings of the 19th International Symposium on Algorithms and Computation, ISAAC 2008, held in Gold Coast, Australia in December 2008.
Algorithms and computation ; 15th international symposium, ISAAC 2004, Hong Kong, China, December 20-22, 2004, Proceedings
This volume contains the proceedings of the 15th Annual International Sym- sium on Algorithms and Computation (ISAAC 2004), held in Hong Kong, 2004. ISAAC is an annual international symposium that covers a wide range of topics,namelyalgorithmsandcomputation. aftar review process the committee selected 76 papers, the decisions being based on originality and relevance to the ?eld of algorithms and computation.
Algorithms and Complexity ; 6th Italian Conference, CIAC 2006, Rome, Italy, May 29-31, 2006, Proceedings
Here are the refereed proceedings of the 6th Italian Conference on Algorithms and Computation, CIAC 2006. The 33 revised full papers presented together with 3 invited papers address such topics as sequential, parallel and distributed algorithms, data structures, approximation algorithms, randomized algorithms, on-line algorithms, graph algorithms, analysis of algorithms, algorithm engineering, algorithmic game theory, computational biology, computational complexity, communication networks, computational geometry, cryptography, discrete optimization, graph drawing, mathematical programming, and quantum algorithms.
