Algorithmic Thinking & Peak Finding in 1D and 2D
53:21MIT 6.006 Lecture 2: Models of Computation, Random Access Machine & Document Distance
48:51MIT 6.006 Lecture 3: Insertion Sort, Binary Insertion & Merge Sort Recurrences
51:19MIT 6.006 Lecture 4: Priority Queues, Binary Heaps & O(n) Build-Max-Heap
52:32MIT 6.006 Lecture 5: Binary Search Trees & Runway Reservation Scheduling
52:39MIT 6.006 Lecture 6: AVL Trees, Tree Rotations & Guaranteed O(log n) Height
51:59MIT 6.006 Lecture 7: Decision-Tree Ω(n log n) Lower Bound, Counting Sort & Radix Sort
52:08MIT 6.006 Lecture 8: Hashing with Chaining, Simple Uniform Hashing & Universal Families
51:15Lecture 9: Table Doubling, Karp-Rabin (6.006)
52:47Lecture 10: Open Addressing, Cryptographic Hashing (6.006)
50:55Lecture 11: Integer Arithmetic, Karatsuba Multiplication (6.006)
47:24Lecture 12: Square Roots, Newton's Method (6.006)
51:17Lecture 13: Breadth-First Search (BFS) (6.006)
50:48Lecture 14: Depth-First Search (DFS), Topological Sort (6.006)
50:31Lecture 15: Single-Source Shortest Paths Problem (6.006)
53:15Lecture 16: Dijkstra (6.006)
51:26Lecture 17: Bellman-Ford (6.006)
48:51Lecture 18: Speeding up Dijkstra (6.006)
53:16Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths (6.006)
51:47Lecture 20: Dynamic Programming II: Text Justification, Blackjack (6.006)
52:12Lecture 21: Dynamic Programming III: Parenthesization, Edit Distance, Knapsack (6.006)
52:41Lecture 22: Dynamic Programming IV: Guitar Fingering, Tetris, Super Mario Bros. (6.006)
49:20Lecture 18: Speeding up Dijkstra (6.006)
This session explores advanced techniques for optimizing Dijkstra's algorithm, focusing on the use of Fibonacci heaps and other priority queue implementations to improve its time complexity.
MIT 6.006 Introduction to Algorithms, Fall 2011
View the complete course: http://ocw.mit.edu/6-006F11
Instructor: Srini Devadas
More courses at http://ocw.mit.edu
Lecture 17: Bellman-Ford (6.006)
Next · Lecture 19Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths (6.006)