Introduction to Algorithms, fourth editionMIT Press, 5 kwi 2022 - 1312 A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout. New for the fourth edition
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Spis treści
| 3 | |
| 17 | |
| 49 | |
DivideandConquer | 76 |
Introduction | 157 |
Quicksort | 182 |
Sorting in Linear Time | 205 |
Medians and Order Statistics | 227 |
Minimum Spanning Trees | 585 |
SingleSource Shortest Paths | 604 |
Maximum Flow | 670 |
Matchings in Bipartite Graphs | 704 |
Introduction | 745 |
Online Algorithms | 791 |
Matrix Operations | 819 |
Linear Programming | 850 |
Introduction | 249 |
Binary Search Trees | 312 |
RedBlack Trees | 331 |
Introduction | 361 |
Greedy Algorithms | 417 |
Amortized Analysis | 448 |
Introduction | 477 |
BTrees | 501 |
Data Structures for Disjoint Sets | 520 |
Introduction | 547 |
Polynomials and the FFT | 877 |
String Matching | 957 |
MachineLearning Algorithms | 1003 |
NPCompleteness | 1042 |
Approximation Algorithms | 1104 |
C | 1159 |
Bibliography | 1227 |
| 1251 | |
Inne wydania - Wyświetl wszystko
Introduction to Algorithms, fourth edition Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest,Clifford Stein Ograniczony podgląd - 2022 |
Introduction to Algorithms, fourth edition Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest,Clifford Stein Podgląd niedostępny - 2022 |
Kluczowe wyrazy i wyrażenia
algorithm amortized cost analysis analyze array assume asymptotic notation B-tree binary search tree block breadth-first search cache miss Chapter compute constant constraints contains data structure define deletion denote depth-first search directed graph divide-and-conquer edge efficient elements equation example execution Exercise Figure flow network given graph G greedy hash function hash table implement input insertion sort integer iteration left child Lemma linear program linked list loop invariant loop of lines M-augmenting path matching matrix max-heap maximum merge sort method minimum spanning tree modulo multiplication negative-weight cycle node nonnegative O(n lgn operations optimal solution optimal substructure parallel partitioning permutation pointer polynomial problem procedure Proof prove pseudocode queue quicksort random recursive calls red-black tree request root Section sequence shortest path Show simple path slot solve subarray subproblems subtree Suppose takes Theorem vertices weight worst-case running