Design and Analysis of Algorithms
CS 3130, Fall 2009, E01, MW, 5:30pm-6:45pm, 417 Clark Hall
Instructor:
Martin Pelikan
E-mail: pelikan@cs.umsl.edu
WWW: http://www.cs.umsl.edu/~pelikan/
Note: Do not call me, I do not respond to phone messages.
Office hours
CCB 320, MW 3:30pm-5:00pm
or by appointment (send email to arrange)
Prerequisites
CS 2250, Math 3000, Math 2450, Stat 1320
Textbook
T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms (Second Edition). MIT Press and McGraw-Hill.
Grading Policy
- Homeworks and programming projects.....50%
- Three tests (in class), no final
- Test 1.....15%
- Test 2.....15%
- Test 3.....20%
Covered topics
- Chapter 1. The role of algorithms in computing.
- Chapter 2. Simple sorting algorithms & algorithm analysis.
- Chapter 3. Growth functions.
- Chapter 4. Recurrences.
- Chapter 5. Probabilistic and randomized algorithms
- Chapters 6-9. Sorting and order statistics.
- Chapters 11-13. Data structures.
- Chapters 15-17. Advanced design and analysis techniques.
Additional info
- If you don't have all the prerequisities, you MUST contact me ASAP.
- Covered topics might evolve over the course of the semester based on progress and interest.
- Visit the course's web page on mygateway regularly.
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Extensions for homeworks only with prior consent of the instructor and only under extraordinary circumstances (at instructor's discretion).
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Grades will be curved at the discretion of the instructor.
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No delayed grade will be given unless really special circumstances are
proven.
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Maintaining confidentiality of student grades policy: Click here.
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Student conduct code including the campus policy on academic dishonesty: Click here.
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Cancellation of student registration policy: Click here.
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Wait list policy: Click here.
- Students who require extended time or other special accomodations for exams due to disabilities must inform me about the situation in the first two weeks of the class. Then, they are responsible for arranging the requested accomodations for each exam with Disability Access Services at UMSL by one week before the exam (I must approve any changes, so start the process well ahead).
Short bio of the instructor:
Martin Pelikan received Ph.D. from the Dept. of Computer Science at the University of Illinois at Urbana-Champaign in 2002. He joined the Dept. of Math and Computer Science at the University of Missouri at St. Louis in August, 2003. Currently, he is an associate professor of computer science. Pelikan's research focuses on genetic and evolutionary computation. He worked at the Slovak University of Technology at Bratislava, the German National Center for Information Technology at Sankt Augustin, the Illinois Genetic Algorithms Laboratory (IlliGAL) at the University of Illinois at Urbana-Champaign, and the Swiss Federal Institute of Technology (ETH) at Zurich. Pelikan's most important contributions to genetic and evolutionary computation are the Bayesian optimization algorithm (BOA), the hierarchical BOA (hBOA), and the scalability theory for BOA and hBOA. BOA and hBOA combine machine learning with genetic and evolutionary algorithms to create optimizers that can solve broad classes of optimization problems in a robust and scalable manner with few or no parameters. BOA and hBOA are among the most advanced and powerful genetic and evolutionary algorithms.