CSc 445 Introduction to Algorithms [ Announcements | Syllabus | Discussion Session | | Web Resources | Research Projects]


CSc 445 Introduction to Algorithms

Homeworks: HW1
HW2
HW3 HW4 HW5 HW6

Time and place TueThu 12:30-1:45, KOFFL 216
Instructor Alon Efrat
alon@cs.arizona.edu
Gould-Simpson 742
(520) 626-8047
Office hours Mon 1:40-2:55. Wed 1:00-2:15.
Assistant Nitin Shinde
nitinshinde@email.arizona.edu
Gould-Simpson 721
Office hours
Tuesday: 10:30 AM - 12:00 PM
Thursday: 11:00 AM - 12:00 PM
This course vs. CSc345 Here is a list of relevant items from CSc345. Some topics you are expected to know in general. other are stricktly needed for this course and you are expected to validy that you master them. Finally, other topics are going to be (re)-discussed in this course. link.
Description After a short illustration of algorithm design and analysis, the course begins by reviewing basic analysis techniques (approximating functions asymptotically, bounding sums, and solving recurrences). We then study problems that are efficiently solvable, focusing on basic design techniques (divide-and-conquer, dynamic programming, greedy, and others), graph algorithms (minimum spanning trees, shortest paths, maximum flow and stable marriage), and geometric algorithms (convex hull, line sweep and closest point-pair) and other cool applications. We conclude with techniques for dealing with approximation algorithms and branch-and-bound algorithms.

The emphasis is on learning algorithm design (the ability to synthesize correct and efficient procedures for new combinatorial problems), acquiring an algorithm repertoire (a toolbox of classic algorithms for well-solved problems), and applying algorithm reduction (the ability to reduce new problems to known problems from your repertoire). These skills are developed through written assignments containing challenging exercises.

Required text Thomas H. Cormen, Charles E. Leiserson, Ron L. Rivest, and Clifford Stein,
Introduction to Algorithms, second edition,
McGraw-Hill, Boston, 2001.
Optional text Steven S. Skiena,
The Algorithm Design Manual,
Springer-Verlag, New York, 1998.
Reserved books Both texts will be put on reserve in the Main Library.
Resources
Schedule There are two exams.
  • Midterm: March 22, 2012.
  • Final:
Grading
         
46%   Homeworks grade
20%   MidTerm exam grade
20%   Final exam grade
11%   Max( MidTerm_exam_grade, Final_exam_grade )
3%   Class participation
Policies On homework, you may discuss general ideas with friends, but your solutions must be written up separately and represent individual work. Use of solutions from previous offerings of the course is not permitted. Homework is due at the start of class; homework turned in once class begins is not accepted.

When you turn in solutions to homeworks and exams, write only on one side of the paper, and staple your pages together. Neatness, and especially conciseness, is required to earn the highest marks. If you cannot solve a problem, state this in your write-up, and write down only what you know to be correct; rambling at length about ideas that don't quite work may cause additional points to be deducted.

Homeworks There are about seven homeworks, which occur roughly after the conclusion of each of the chapters. The homework with the lowest score will be ignored.
Honor projects Any students (including non-honors) can commit to be involved in a research project. The grade of the project would substitute 20% of the final grade, and the student can skip at least 2 of the homeworks. More information is given in class.
Announcements:

Announcements are published on the D2L link


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