Design and Analysis of Algorithms (2015)

6.046 introduces students to the design of computer algorithms, as well as analysis of sophisticated algorithms. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

Lecture 24: Cache-Oblivious Algorithms: Searching & Sorting

In this lecture, Professor Demaine continues with cache-oblivious algorithms, including their applications in searching and sorting.

01-03
01:17:41

Lecture 23: Cache-Oblivious Algorithms: Medians & Matrices

In this lecture, Professor Demaine introduces cache-oblivious algorithms.

01-03
01:20:27

Recitation 11: Cryptography: More Primitives

In this recitation, problems related to cryptography are discussed.

01-03
49:30

Lecture 22: Cryptography: Encryption

In this lecture, Professor Devadas continues with cryptography, introducing encryption methods.

01-03
01:24:14

Lecture 21: Cryptography: Hash Functions

In this lecture, Professor Devadas covers the basics of cryptography, including desirable properties of cryptographic functions, and their applications to security.

01-03
01:22:00

Recitation 10: Distributed Algorithms

In this recitation, problems related to distributed algorithms are discussed.

01-03
50:18

Lecture 20: Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees

In this lecture, Professor Lynch introduces asynchronous distributed algorithms.

01-03
01:12:03

Lecture 19: Synchronous Distributed Algorithms: Symmetry-Breaking

In this lecture, Professor Lynch introduces synchronous distributed algorithms.

01-03
01:17:33

Recitation 9: Approximation Algorithms: Traveling Salesman Problem

In this recitation, problems related to approximation algorithms are discussed, namely the traveling salesman problem.

01-03
31:59

Lecture 18: Complexity: Fixed-Parameter Algorithms

In this lecture, Professor Demaine tackles NP-hard problems using fixed-parameter algorithms.

01-03
01:17:43

Lecture 17: Complexity: Approximation Algorithms

In this lecture, Professor Devadas introduces approximation algorithms in the context of NP-hard problems.

01-03
01:21:08

Recitation 8: NP-Complete Problems

In this recitation, problems related to NP-Completeness are discussed.

01-03
45:46

Lecture 16: Complexity: P, NP, NP-completeness, Reductions

In this lecture, Professor Demaine introduces NP-completeness.

01-03
01:25:25

Lecture 15: Linear Programming: LP, reductions, Simplex

In this lecture, Professor Devadas introduces linear programming.

01-03
01:22:27

Recitation 7: Network Flow and Matching

In this recitation, problems related to Network Flow and Matching are discussed.

01-03
51:12

Lecture 14: Incremental Improvement: Matching

In this lecture, Professor Devadas continues with the topic of network flow.

01-03
01:22:32

Lecture 13: Incremental Improvement: Max Flow, Min Cut

In this lecture, Professor Devadas introduces network flow, and the Max Flow, Min Cut algorithm.

01-03
01:22:57

Recitation 6: Greedy Algorithms

In this recitation, problems related to greedy algorithms are discussed.

01-03
22:24

Lecture 12: Greedy Algorithms: Minimum Spanning Tree

In this lecture, Professor Demaine introduces greedy algorithms, which make locally-best choices without regards to the future.

01-03
01:22:09

Lecture 11: Dynamic Programming: All-Pairs Shortest Paths

In this lecture, Professor Demaine covers different algorithmic solutions for the All-Pairs Shortest Paths problem.

01-03
01:21:49

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