ynamic order statistics OS-SELECT(i, S): returns the i th smallest element in the dynamic set S. OS-RANK(, S): returns the rank ofx E S in the sorted order of s s elements IDEA: Use a red-black tree for the set S, but keep subtree sizes in the nodes

1. 一般方法 2. 二分检索 3. 找最大和最小元素 4. 归并分类 5. 快速分类 6. 选择问题 7. 斯特拉森矩阵乘法

a weakness of hashing Problem: For any hash function h, a set of keys exists that can cause the average access time of a hash table to skyrocket An adversary can pick all keys from tkeU: h(k)=i for some slot i IDEA Choose the hash function at random independently of the keys

How fast can we sort? All the sorting algorithms we have seen so far are comparison sorts: only use comparisons to determine the relative order of elements E. g, insertion sort, merge sort, quicksort heapsort The best worst-case running time that weve seen for comparison sorting is O(nIgn) Is o(nlgn) the best we can do?

4.1 基本概念 4.2 基本遗传算法 4.3 遗传算法应用举例 4.4 遗传算法的特点与优势

1.1数据结构的基本概念 1.2数据结构类型 1.3抽象数据类型 1.4数据与数据结构 1.5算法 1.6算法分析

南京大学：《信息与计算科学导论》课程教学资源（课件讲稿）递归算法与递归方程 Recursive Algorithm and Recurrence Relations

杭州电子科技大学：《人工智能导论》课程教学资源（PPT课件讲稿）第四讲 遗传算法

一、简单回顾一维牛顿法 二、收敛性检验 三、多维牛顿法 四、基本算法

8.1 图论问题 8.2 算法复杂性问题 8.3 计算机智能问题 8.4 并发控制问题