Introduction and Proofs (MIT 6.042J, Lecture 1)
44:09Mathematical Induction (MIT 6.042J, Lecture 2)
1:19:25Strong Induction (MIT 6.042J, Lecture 3)
1:22:00Number Theory I (MIT 6.042J, Lecture 4)
1:20:24Number Theory II (MIT 6.042J, Lecture 5)
1:18:45Graph Theory and Coloring (MIT 6.042J Mathematics for Computer Science, Lecture 6)
1:22:51Matching Problems (MIT 6.042J Mathematics for Computer Science, Lecture 7)
1:22:40Graph Theory II: Minimum Spanning Trees (MIT 6.042J, Lecture 8)
1:23:26Lecture 9: Communication Networks (6.042J)
1:23:25Lecture 10: Graph Theory III (6.042J)
1:22:50Lecture 11: Relations, Partial Orders, and Scheduling (6.042J)
1:04:00Lecture 12: Sums (6.042J)
1:18:22Lecture 13: Sums and Asymptotics (6.042J)
1:23:40Divide and Conquer Recurrences (MIT 6.042J, Lecture 14)
1:22:46Lecture 15: Linear Recurrences (6.042J)
1:18:20Lecture 16: Counting Rules I (6.042J)
1:20:02Lecture 17: Counting Rules II (6.042J)
1:25:24Lecture 18: Probability Introduction (6.042J)
1:23:56Lecture 19: Conditional Probability (6.042J)
1:21:46Lecture 20: Independence (6.042J)
1:22:02Lecture 21: Random Variables (6.042J)
1:22:59Lecture 22: Expectation I (6.042J)
1:23:54Divide and Conquer Recurrences (MIT 6.042J, Lecture 14)
This lecture systematically introduces the analysis of recurrence relations arising from divide and conquer algorithms. Professor Leighton covers methods for solving these recurrences, including the Master Theorem.
Lecture 14: Divide and Conquer Recurrences
Instructor: Tom Leighton
Lecture 13: Sums and Asymptotics (6.042J)
Next · Lecture 15Lecture 15: Linear Recurrences (6.042J)