CS 787 (Fall 2010) Reading List

Here are the primary sources for this year's 787 lectures. In many cases, we will cover only a few ideas from a given paper. This list will be added to as the semester proceeds.

Links given are to PDF or postscript versions, if publicly available. If you are on campus, the UW Library catalog (MadCat, then the FindIT button) will give you links to many journals and conference proceedings. You can also try ArXiv, Google Scholar, etc., although these are less comprehensive and likely to reach preliminary versions of papers. Older works may require a hike to the library (good exercise).

Algorithm design strategies:

• Using Induction to Design Algorithms, Udi Manber, CACM 31, pp. 1300-1313, 1988.
• How to Design Dynamic Programming Algorithms Sans Recursion, Kirk Pruhs, SIGACT News 29(1), pp. 32-35, March 1988.
• Multiplication of Multidigit Numbers on Automata, A. Karatsuba and Y. Ofman, Soviet Physics Doklady, v. 7, 1963, pp. 595-596. [Translation of Doklady Akad. Nauk SSSR 145, pp. 293-294, 1962.]

Linear Programming:

• Maximization of a Linear Function of Variables Subject to Linear Inequalities, George Dantzig, pp. 339-347 of Activity Analysis of Production and Allocation, ed. T.J. Koopmans, John Wiley and Sons, 1951.
• Two Lectures on Linear Programming by Richard Karp, here and here.
• Smoothed Analysis of Algorithms: Why the Simplex Algorithm Usually Takes Polynomial Time, Daniel Spielman and Shang-Hua Teng, Proc. 32nd ACM Symposium on Theory of Computing (STOC), pp. 296-305, 2001.

Flows and Matchings (aka "Bipartite Programming"):

• Sections 26.1-26.3 of Introduction to Algorithms, 2nd edn., by T. Cormen, C. Leiserson, and R. Rivest.
• A New Property and a Faster Algorithm for Baseball Elimination, K. Wayne, Proc. 10th Ann. ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 815-819, 1999.
• Kuhn's "Hungarian" Assignment Algorithm, Sans Dual Variables, E. Bach, Manuscript, 2009.

Greedy Algorithms and Matroids

• Sections 7.1-7.7 of Combinatorial Optimization: Networks and Matroids, by E.L. Lawler.
• On greedy algorithms that succeed, A. Hoffman, in I. Anderson, ed., Surveys in Combinatorics, London Math Soc. Lecture Notes series 103, 1985, pp. 97-112.
• Matroids and the greedy algorithm, J. Edmonds, Math. Programming 1, 1971, pp. 127-136.

Randomization

• E. Bach and J. Shallit, Algorithmic Number Theory, pp. 157-158.
• Fast probabilistic algorithms for verification of poynomial identities, J. Schwartz, Journal of the ACM, 1980.
• Matching is as easy as matrix inversion, K. Mulmuley, U. Vazirani, and V. Vazirani, Combinatorica 7, 1987, pp. 105-113.
• Chapter 9 of R. E. Tarjan, Data Structures and Network Algorithms, SIAM, 1983.
• Paths, trees, and flowers, J. Edmonds, Canadian J. Math., 1965
• Randomized rounding: a technique for provably good algorithms and algorithmic proofs, P. Raghavan and C. Thompson, Combinatorica 7, 1987, pp. 365-374.
• New 3/4-approximation algorithms for MAX SAT, M. X. Goemans and D. P. Williamson, SIAM J. Discrete Math., v. 7, 1994, 656-666.