Course Number: 3460:635
Course Name: Advanced Algorithms and Complexity Theory
Course Credits: 3
Schedule: Alternate Springs
Syllabus Date: October 10, 2007
Prepared By: Dr. Duan(modified by Dr. Pelz)
Prerequisites: Admission to Computer Science master’s program or permission.
Text: Introduction to Algorithms, 2nd Edition, by T.H. Cormen, C.E. Leiserson, R.L.
Rivest, and C. Stein, McGraw-Hill, 2001.
Bulletin Description: Topics include a number of advanced topics in algorithms
including network flows, matrix operations, linear programming, fast Fourier transform,
number-theoretic algorithms, string comparison, computational geometry, singular value
decomposition, NP-complete and intractable problems, and approximation techniques.
Detailed Description: The course focuses on a number of advanced topics in algorithms
including network flows, matrix operations, linear programming, fast Fourier transform,
number-theoretic algorithms, string comparison, computational geometry, singular value
decomposition, NP-complete and intractable problems, and approximation techniques.
The focuses are on both fundamental techniques and their applications. Applications
include string matching and its role in biological sequence alignment; flow network and
its application in microarray data analysis; singular value decomposition and its
application in data compression and visualization.
Course Goals: To introduce students to the advanced techniques in the design and
analysis of algorithms and some state-of-art applications.
Topics: Topics include network flows, matrix operations, linear programming, fast
Fourier transform, number-theoretic algorithms, string comparison, computational
geometry, singular value decomposition, NP-complete and intractable problems, and
approximation techniques.
Computer Usage: Typically 3 or 4 programming assignments involving maximum flow
algorithm, Gaussian elimination, RSA algorithm, and string comparison.
References:
1. Donald Knuth, The Art of Computer Programming, Vol. 1-3. Addison-Wesley, 1997.
2. Alfred Aho, John Hopcroft, Jeffrey Ullman, The Design and Analysis of Computer
Algorithms, Addison-Wesley, 1974.
3. Richard Durbin, Sean Eddy, Anders Krogh, Graeme Mitchison, Biological Sequence
Analysis : Probabilistic Models of Proteins and Nucleic Acids, Cambridge University
Press, 1999.