|
Features
- 1. Introduction to Algorithms
- 2. Efficiency of algorithm
- 3. Analysis of insertion sort
- 4. Insertion sort
- 5. The divide-and-conquer approach
- 6. Analyzing divide-and-conquer algorithms
- 7. Asymptotic notation
- 8. Asymptotic notation in equations and inequalities
- 9. Standard notations and common functions
- 10. The hiring problem
- 11. Indicator random variables
- 12. Balls and bins
- 13. Probabilistic analysis and further uses of indicator random variables
- 14. Streaks
- 15. The on-line hiring problem
- 16. Overview of Recurrences
- 17. The substitution method for recurrences
- 18. The recursion-tree method
- 19. The master method
- 20. Proof of the master theorem
- 21. The proof for exact powers
- 22. Floors and ceilings
- 23. Randomized algorithms
- 24. Heaps
- 25. Maintaining the heap property
- 26. Building a heap
- 27. The heapsort algorithm
- 28. Priority queues
- 29. Description of quicksort
- 30. Performance of quicksort
- 31. A randomized version of quicksort
- 32. Analysis of quicksort
- 33. Lower bounds for sorting
- 34. Counting sort
- 35. Radix sort
- 36. Minimum and maximum
- 37. Selection in expected linear time
- 38. Bucket sort
- 39. Selection in worst-case linear time
- 40. Stacks and queues
- 41. Linked lists
- 42. Implementing pointers and objects
- 43. Representing rooted trees
- 44. Direct-address tables
- 45. Hash tables
- 46. Hash functions
- 47. Open addressing
- 48. Perfect hashing
- 49. introduction to binary search tree
- 50. Querying a binary search tree
- 51. Insertion and deletion
- 52. Randomly built binary search trees
- 53. Red-Black Trees
- 54. Rotations of red black tree
- 55. Insertion in red black tree
- 56. Deletion in red black tree
- 57. Dynamic order statistics
- 58. Augmenting a Data Structure
- 59. Interval Trees
- 60. Overview of Dynamic Programming
- 61. Assembly-line scheduling
- 62. Matrix-chain multiplication
- 63. Elements of dynamic programming
- 64. Longest common subsequence
- 65. Optimal binary search trees
- 66. Greedy Algorithms
- 67. Elements of the greedy strategy
- 68. Huffman codes
- 69. Theoretical foundations for greedy methods
- 70. A task-scheduling problem
- 71. Aggregate analysis
- 72. The accounting method
- 73. The potential method
- 74. Dynamic tables
- 75. B-Trees
- 76. Definition of B-trees
- 77. Basic operations on B-trees
- 78. Deleting a key from a B-tree
- 79. Binomial Heaps
- 80. Operations on binomial heaps
- 81. Fibonacci Heaps
- 82. Mergeable-heap operations
- 83. Decreasing a key and deleting a node
- 84. Bounding the maximum degree
- 85. Data Structures for Disjoint Sets
- 86. Linked-list representation of disjoint sets
- 87. Disjoint-set forests
- 88. Analysis of union by rank with path compression
- 89. Representations of graphs
- 90. Breadth-first search
- 91. Depth-first search
- 92. Topological sort
- 93. Strongly connected components
- 94. Minimum Spanning Trees
- 95. Growing a minimum spanning tree
- 96. The algorithms of Kruskal and Prim
- 97. Single-Source Shortest Paths
- 98. The Bellman-Ford algorithm
- 99. Single-source shortest paths in directed acyclic graphs
- 100. Dijkstra's algorithm
- 101. Difference constraints and shortest paths
- 102. Shortest paths and matrix multiplication
- 103. The Floyd-Warshall algorithm
- 104. Johnson's algorithm for sparse graphs
- 105. Flow networks
- 106. The Ford-Fulkerson method
- 107. Maximum bipartite matching
- 108. Push-relabel algorithms
- 109. The relabel-to-front algorithm
- 110. Comparison networks
*If this is not the "Design & Analysis of Algorithm" product you were looking for, you can check the other results by clicking this link. Details were last updated on Nov 13, 2024 15:12 +08.