It aims to provide a broad and accessible coverage of the interactions between discrete and continuous mathematics, in the perspective of detailed analyses of combinatorial models, as may be present in the applied sciences as well as in analysis of algorithms. The core theory of analytic ...
clear delineation of analysis methods, "Introduction to the Design and Analysis of Algorithms" presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the m...
This textbook covers the mathematical foundations of the analysis of algorithms. The gist of the book is how to argue, without the burden of excessive formalism, that a given algorithm does what it is supposed to do. The two key ideas of the proof of correctness, induction and invariance, ...
同年,普林斯顿的 Rebert Sedgewick 向 SIAM 投递了一篇讨论奇偶归并排序的文章 [2],其中给出了数据在排序过程中平均交换次数的简洁表达式。Sedgewick 通过渐进分析获得的这个表达式后来被发现和 Flajolet 用于评估寄存器数量的式子具有同一性。Flajolet 后来给 Sedgewick 写信说:> I believe that we have a formula in ...
Communication network design, VLSI layout and DNA sequence analysis are important and challenging problems that cannot be solved by naive and straightforward algorithms. Thus, it is critical for a computer scientist to have a good knowledge of algorithm design and analysis. This book presents algorithm...
— Mathematical Reviews "The book covers the important mathematical tools used in computer science, especially in the exact analysis of algorithms. A wide range of topics are covered, from the binomial theorem to the saddle point method and Laplace's techniques for asymptotic analysis...The book ...
The book also includes over 50 practical programming algorithms to put the concepts to work with time-oriented data. Like several other titles on this list, this is a solid textbook for graduate studies as well as a handy reference guide for researchers. 6. “Practical Time Series Forecasting...
book features fully worked-out exercises, without the help of a computer, illustrating the constructions of correspondence analysis. It gives details of how to prepare, read and interpret computer results, including a complete FORTRAN program listing of the basic algorithms of factor analysis and ...
Updated Oct 2, 2024 Jupyter Notebook DataCanvasIO / YLearn Star 396 Code Issues Pull requests Discussions YLearn, a pun of "learn why", is a python package for causal inference causality causality-analysis causal-inference causal-models uplift-modeling uplift causality-algorithms causal-discov...
Along with finite differences and finite elements, spectral methods are one of the three main methodologies for solving partial differential equations on computers. This book provides a detailed presentation of basic spectral algorithms, as well as a systematical presentation of basic convergence theory ...