Computer Science 284/484
Instructor: Daniel Stefankovic
Class: Tuesday, Thursday 12:30pm-13:45pm, Wilmot 116.
Instructor office hours (Wegmans 2315): Tuesday, Thursday 2pm - 3pm.
TA: Ben Reber.
Textbooks: there is no required textbook; see each section for the recommended reading (mostly online; I will also supply handouts).
Other resources/recommended reading:
- [CLRS09] Introduction to Algorithms (3rd edition), T. Cormen, C. Leiserson, R. Rivest, and C. Stein, 2009.
- [K91] The Design and Analysis of Algorithms, D. Kozen, 1991.
- [KT05] Algorithm Design, J. Kleinberg and E. Tardos, 2005.
- [AHU74] The Design and Analysis of Computer Algorithms, A. Aho, J. Hopcroft, J. Ulman, 1974.
- [MU05] Probability and Computing: Randomized Algorithms and Probabilistic Analysis, M. Mitzenmacher, E. Upfal, 2005.
- [MR95] Randomized Algorithms, R. Motwani, P. Raghavan, 1995.
- [H02] Finite Markov chains and algorithmic applications, O. Haggstrom, 2002.
- [G97] Counting, sampling and integrating: algorithms and complexity, M. Jerrum, 2003.
- [WS11] The Design of Approximation Algorithms, D.Williamson, D. Shmoys, 2011
- [V04] Approximation Algorithms, V. Vazirani, 2004.
- [BE98] Online Computation and Competitive Analysis, A. Borodin, R. El-Yaniv, 1998.
- [M05] Data Streams: Algorithms and Applications, S. Muthukrishnan, 2005.
- [BCKO08] Computational Geometry: Algorithms and Applications, M. de Berg, O. Cheong, M. van Kreveld, M. Overmars, 2008.
- [PS85] Computational Geometry: An Introduction, F. Preparata, M. Shamos, 1985.
- [M93] Computational Geometry: An Introduction Through Randomized Algorithms, K. Mulmuley, 1993.
- [G97] Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology, D. Gusfield, 1997.
TOPIC 1: Max-Flow
Jan. 16 Th - Max Flow I (basics, Ford-Fulkerson, min-cut max-flow)
Jan. 21 Tu - Max Flow II (Edmonds Karp)
Jan. 23 Th - Max Flow III (Push Relabel)
homework 1 (max flow) - due Feb. 6
TOPIC 2: Linear Programming/Semidefinite programming
TOPIC 3: Computational Geometry
Feb. 20 Th - Computational Geometry I (sweep technique)
Feb. 25 Tu - Computational Geometry II (convex hulls)
Feb. 27 Th - Computational Geometry III (closest pair of points)
Mar. 3 Tu - Computational Geometry IV (Voronoi diagrams)
homework 4 (computational geometry) - due Mar. 19
TOPIC 4: String Algorithms
Mar. 5 Th - String Algorithms I (Suffix Trees)
Mar. 10 Tu - SPRING BREAK
Mar. 12 Th - SPRING BREAK
Mar. 17 Tu - String Algorithms II (Suffix Trees)
Mar. 19 Th - String Algorithms III (Suffix Arrays)
Mar. 24 Tu - String Algorithms IV (Suffix Arrays)
homework 5 (string algorithms) - due Apr. 2
TOPIC 5: Streaming Algorithms
Mar. 26 Th - Probability I
Mar. 31 Tu - Probability II
Apr. 2 Th - Streaming Algorithms I (distinct elements)
Apr. 7 Tu - Streaming Algorithms II (sketching)
Apr. 9 Th - Streaming Algorithms III (frequency moments)
Apr. 14 Tu - Streaming Algorithms IV
homework 6 (streaming algorithms) - due Apr. 23
TOPIC 6: Something Fun
Apr. 16 Th - TBD
Apr. 21 Tu - TBD
Apr. 23 Th - TBD
Apr. 28 Tu - TBD
The grade for the course is based on the homework (theoretical and applied; there will be 6 problem sets); there are no exams.
- Theoretical homework should be typeset (LaTeX preferred) and emailed to the instructor by the deadline (specific for each assignment). You may work with other people on the theoretical homework, but you must each write up your solutions separately (without any written aid). If you work with other people, indicate who you worked with on your solution.
- No late homework will be accepted without instructor's permission (a permission must be requested at least 24 hours before the due date).
This course follows
The University Policy on Academic Honesty