Introduction to Algorithms (Fall 2005) (M-I-T)

• Lecture 1: Administrivia; Introduction; Analysis of Algorithms, Insertion Sort, Mergesort (M-I-T)
• Lecture 2: Asymptotic Notation; Recurrences; Substitution, Master Method (M-I-T)
• Lecture 3: Divide-and-Conquer: Strassen, Fibonacci, Polynomial Multiplication (M-I-T)
• Lecture 4: Quicksort, Randomized Algorithms (M-I-T)
• Lecture 5: Linear-time Sorting: Lower Bounds, Counting Sort, Radix Sort (M-I-T)
• Lecture 6: Order Statistics, Median (M-I-T)
• Lecture 7: Hashing, Hash Functions (M-I-T)
• Lecture 8: Universal Hashing, Perfect Hashing (M-I-T)
• Lecture 9: Relation of BSTs to Quicksort - Analysis of Random BST (M-I-T)
• Lecture 10: Red-black Trees, Rotations, Insertions, Deletions (M-I-T)
• Lecture 11: Augmenting Data Structures, Dynamic Order Statistics, Interval Trees (M-I-T)
• Lecture 12: Skip Lists (M-I-T)
• Lecture 13: Amortized Algorithms, Table Doubling, Potential Method (M-I-T)
• Lecture 14: Competitive Analysis: Self-organizing Lists (M-I-T)
• Lecture 15: Dynamic Programming, Longest Common Subsequence (M-I-T)
• Lecture 16: Greedy Algorithms, Minimum Spanning Trees (M-I-T)
• Lecture 17: Shortest Paths I: Properties, Dijkstra's Algorithm, Breadth-first Search (M-I-T)
• Lecture 18: Shortest Paths II: Bellman-Ford, Linear Programming, Difference Constraints (M-I-T)
• Lecture 22: Advanced Topics (M-I-T)
• Lecture 23: Advanced Topics (cont.) (M-I-T)
• Lecture 24: Advanced Topics (cont.) (M-I-T)
• Lecture 25: Advanced Topics (cont.) - Discussion of Follow-on Classes (M-I-T)