Andrew McGregor

Welcome to the Fall 2012 homepage for CMPSCI 611 - Advanced Algorithms.

• Instructor:
  • Andrew McGregor. Email: mcgregor at cs.
  • Office hours: Wednesday 10-11 in CMPS 334 or by appointment.
  
  
• TA:
  • Kun Tu. Email: kuntu at cs.
  • Office hours: Monday 1-2 in Common Room (Computer Science Department) or by appointment.
  
  
• Textbook: The required textbook will be "Lecture Notes from CMPSCI 611" by Prof. Micah Adler and this will be available from the Textbook Annex. See here for a list corrections and typos. Other books you might find generally useful include:
  • Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein (Library has the e-book)
  • Algorithm Design by Kleinberg and Tardos
  • Algorithms by Dasgupta, Papadimitriou, Vazirani (See here for penultimate draft.)
  You may also find sections of the following books helpful:
  • Randomized Algorithms by Motwani and Raghavan (Library has the e-book)
  • Probability and Computing by Mitzenmacher and Upfal (Library has the e-book)
  • Approximation Algorithms by Vazirani (Library has the e-book if you can read French)
  
  
• Homeworks and Exams:
  • Homework 1: Posted 9/11, Due 9/25
  • Homework 2: Posted 9/27, Due 10/11
  • Homework 3: Posted 10/20, Due 11/1
  • Homework 4: Posted 11/6, Due 11/20
  • Homework 5: Posted 11/20, Due 12/6
  • Midterm: In class on 16 Oct. The exam will cover the first 11 lectures. Here are the solutions.
  • Final: In Engineering Lab II Room 119, 10:30am to 12:30pm, 13 Dec. The exam will cover all the material.
  • Support Material:
    • If you would like to write your homework solutions in LaTeX, here's a template (and here's a compiled version.)
    • Practice Midterms: 2009 Midterm, 2009 Solutions, 2005 Material, 2006 Material 2010 Midterm and 2010 Solutions
    • Practice Finals: 2010 Final, 2009 Final, 2009 Rough Solutions, 2005 Practice Final and 2005 Solutions
  
  Late Policy: Homeworks are due at the start of class by email. Late policy is that you're allowed to hand in at most one of the homework 48 hours late. You don't even need a good excuse! However, if later in the semester you don't hand in a homework on time, even if you have the best excuse in the world, then you'll get no credit for the second homework. Therefore, since you can't tell what might happen in the future, I'd suggest that you don't use your "lifeline" prematurely.
  
  Honesty and Collaboration Policy: Violating any of the following rules risks an automatic F. Ask if you're unsure about any of the policies.
  • Homework: Collaborating with at most two other students in the homework is allowed but answers must be written independently and you should mention who you worked with. You're not allowed to use material from the web (or indeed any material except from that listed on the course page) or talk about the homework with anybody outside your collaboration group (aside from the lecturer or TA.)
  • Quizzes: No collaboration! But you can consult any material you like.
  • Exams: Closed book and no collaboration.
  
  
• Schedule and Slides: Here's an approximate schedule for the course. Note that this'll be updated as we go along depending on our progress and, hopefully, we'll get to squeeze in a couple of extra topcs. I'll add slides after each class (some links will be dead until the slides are added).
  
  

  Lecture	Date	Topic	Reading and Background	Assigned	Due
  1	4 Sept	Preliminaries, Mergesort, Master Theorem	Section 1, 2.1, 2.2
  2	6 Sept	Strassen's Matrix Multiplication Algorithm, Closest Pairs	Section 2.3, 2.4. A blog post describing recent progress on matrix multiplication.	Q1
  3	11 Sept	The Fast Fourier Transform	Section 2.5	HW1	Q1
  4	13 Sept	Minimum Spanning Trees, Subset Systems	Section 3.1, 3.2
  5	18 Sept	Matroids	Section 3.3
  6	20 Sept	Bipartite Matchings	Section 3.4
  7	25 Sept	The Union-Find Problem, Kruskal's Algorithm	Section 3.5	Q2	HW1
  8	27 Sept	Knapsack Problem, Dynamic Programming, Floyd-Warshall	Section 4.1-4.4	HW2	Q2
  9	2 Oct	Dijkstra	Section 4.5
  10	4 Oct	Seidel	Section 4.6
  -	9 Oct	No Class (Monday Schedule)
  11	11 Oct	Network Flow, Ford-Fulkerson Algorithm	Section 5.1-5.4		HW2
  -	16 Oct	Midterm	First five chapters.
  12	18 Oct	Quicksort, Karger's Algorithm	Section 6.1	HW3
  -	23 Oct	No Class
  -	24 Oct	Distinguished Department Lecture: Algorithms, Graph Theory, and the Solution of Laplacian Linear Equations (Daniel Spielman, Yale)	A video about Daniel Spielman's MacArthur Fellowship
  13	25 Oct	Karger's Algorithm and Polynomial Identities	Section 6.2, 6.3
  14	30 Oct	Tail Inequalities and Lazy Select	Section 6.5
  15	1 Nov	Chernoff Bounds and Balls and Bins	Section 6.5, Video showing concentration of binomial distribution		HW3
  16	6 Nov	Hash Functions and Count-Min Sketch	Original Paper	HW4
  17	8 Nov	NP-Completeness	Section 7.1-7.3.4, A Vote on P=NP
  18	13 Nov	Subset Sum and Approximation Algorithms
  19	15 Nov	P versus NP, Approximations, Independent Set Problem
  20	20 Nov	More Approximations, Metric TSP Problem		HW5, Q3	HW4
  -	22 Nov	No class (Thanksgiving)			Q3
  21	27 Nov	Set Cover Problem, Poly-Time Approximation Scheme
  22	29 Nov	Linear Programming, Simplex Method		Q4
  23	4 Dec	Analysis of the Simplex Method			Q4
  24	6 Dec	Review and Any Question			HW5
  -	13 Dec 10:30am - 12:30pm	Final Exam	First nine chapters.