MIT 6.046J / 18.410J Introduction to Algorithms - Fall 2005

MIT 6.046J / 18.410J Introduction to Algorithms - Fall 2005

23 Lectures ยท Sep 7, 2005

About

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Course Homepage 6.046J / 18.410J Introduction to Algorithms (SMA 5503) Fall 2005

Course features at MIT OpenCourseWare page: *Syllabus *Calendar *Readings *Assignments *Exams *Download Course Materials

Complete MIT OCW video collection at MIT OpenCourseWare - VideoLectures.NET

Uploaded videos:

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01:20:32

Lecture 1: Administrivia, Introduction, Analysis of Algorithms, Insertion Sort, ...

Charles E. Leiserson

Feb 10, 2009

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133275 Views

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01:10:28

Lecture 2: Asymptotic Notation, Recurrences, Substitution, Master Method

Erik Demaine

Feb 10, 2009

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126978 Views

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01:08:32

Lecture 3: Divide-and-Conquer: Strassen, Fibonacci, Polynomial Multiplication

Erik Demaine

Feb 10, 2009

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54383 Views

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01:20:30

Lecture 4: Quicksort, Randomized Algorithms

Charles E. Leiserson

Feb 10, 2009

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62767 Views

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01:16:46

Lecture 5: Linear-time Sorting: Lower Bounds, Counting Sort, Radix Sort

Erik Demaine

Feb 10, 2009

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40194 Views

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01:08:48

Lecture 6: Order Statistics, Median

Charles E. Leiserson

Feb 10, 2009

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31721 Views

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01:17:35

Lecture 7: Hashing, Hash Functions

Charles E. Leiserson

Feb 10, 2009

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43176 Views

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01:19:46

Lecture 8: Universal Hashing, Perfect Hashing

Charles E. Leiserson

Feb 10, 2009

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39278 Views

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01:21:21

Lecture 9: Relation of BSTs to Quicksort, Analysis of Random BST

Erik Demaine

Feb 10, 2009

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22763 Views

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01:23:48

Lecture 10: Red-black Trees, Rotations, Insertions, Deletions

Erik Demaine

Feb 10, 2009

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152680 Views

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01:23:44

Lecture 11: Augmenting Data Structures, Dynamic Order Statistics, Interval Trees...

Charles E. Leiserson

Feb 10, 2009

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31318 Views

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01:25:31

Lecture 12: Skip Lists

Erik Demaine

Feb 10, 2009

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47069 Views

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01:19:05

Lecture 13: Amortized Algorithms, Table Doubling, Potential Method

Charles E. Leiserson

Feb 10, 2009

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39684 Views

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01:14:27

Lecture 14: Competitive Analysis: Self-organizing

Charles E. Leiserson

Feb 10, 2009

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13695 Views

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01:10:56

Lecture 15: Dynamic Programming, Longest Common Subsequence

Charles E. Leiserson

Feb 10, 2009

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80631 Views

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01:24:06

Lecture 16: Greedy Algorithms, Minimum Spanning Trees

Charles E. Leiserson

Feb 10, 2009

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57621 Views

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01:24:33

Lecture 17: Shortest Paths I: Properties, Dijkstra's Algorithm, Breadth-first Se...

Erik Demaine

Feb 10, 2009

 ยท 

64751 Views

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01:17:13

Lecture 18: Shortest Paths II: Bellman-Ford, Linear Programming, Difference Cons...

Erik Demaine

Feb 10, 2009

 ยท 

105464 Views

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01:14:55

Lecture 19: Shortest Paths III: All-pairs Shortest Paths, Matrix Multiplication,...

Erik Demaine

Feb 10, 2009

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33758 Views

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01:15:07

Lecture 22: Advanced Topics

Charles E. Leiserson

Feb 10, 2009

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18152 Views

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01:17:03

Lecture 23: Advanced Topics (cont.)

Charles E. Leiserson

Feb 10, 2009

 ยท 

10713 Views

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01:24:46

Lecture 24: Advanced Topics (cont.)

Erik Demaine

Feb 10, 2009

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10439 Views

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01:25:20

Lecture 25: Advanced Topics (cont.), Discussion of Follow-on Classes

Erik Demaine

Feb 10, 2009

 ยท 

10748 Views

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