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Lectures - Teaching Assistant - Resources
Description:
This
course is an introductory graduate course on the design and analysis of
algorithms. The course builds on an undergraduate-level study of the analysis
and implementation of data structures and algorithms (COMPSCI 201). The goal is
to introduce a number of important algorithm design techniques as well as basic
algorithms that are interesting both from a theoretical and also practical
point of view. We will cover basic algorithm design techniques such as
divide-and-conquer, dynamic programming, and greedy techniques for
optimization. We will cover techniques for proof of the correctness of algorithms
and also asymptotic analysis of algorithm time bounds by the solution of
recurrence equations. We will apply these design and analysis techniques to
derived algorithms for a variety of tasks such as sorting, searching, and graph
problems. Some specific algorithm topics include: deterministic and randomized
sorting and searching algorithms, depth and breadth first search graph
algorithms for finding paths and matchings, and algebraic algorithms for fast
multiplication and linear system solving.
Prerequisites:
An
undergraduate-level course on the analysis and implementation of data
structures and algorithms (COMPSCI 201 or equivalent) and also four semesters
of college mathematics. This course requires a certain amount of mathematical
sophistication (e.g., as required to solve recurrence equations). A quiz on
recurrence equations early in the course will provide you with some feedback on
whether your mathematics training will suffice. If you feel that you may not
have sufficient background, please talk with the instructor John Reif.
Meetings:
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Times: Tues & Thurs 3:05 PM – 4:20
PM Room: Schiciano Auditorium (Side B) 1466 Fitzpatrick Center |
Instructor:
Professor John Reif |
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Office: |
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D223 LSRC
Building |
Phone: |
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919-660-6568 |
Email: |
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Web page: |
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Office hours: |
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Tues, Thurs:
4:20 - 5:30 PM |
TAs: Shalin Shah, Hang Yuan, and Tianqi
Song
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Course
material:
á Solutions to Selected exercises and problems in
CLRS
Optional
auxiliary reading (other good reference books):
Course
synopsis:
Summary
of topics covered and lecture notes:
Consult
the schedule of Lectures for a list of topics and a copy of lecture notes
for the lectures to date. Other handouts can be found in the handouts directory. See resources page for additional information.
Homework
assignments:
Homeworks
are due roughly every second week and must be turned in before class on
Wednesday of the week they're due. No credit is given for late
solutions. For exceptional circumstances, see John Reif in advance,
rather than after the due time.
Details
about proper style for writing up homework solutions and some guidelines for grading are
available.
It is
recommended but not required that LaTeX be used for typesetting homework
problems.
Honor code: For homework
problems, discussion among students is permitted, but students must write up
solutions independently on their own. No materials or sources from prior years'
classes or from the Internet can be consulted. During every exam: all
calculators, computers, cell phones, wireless or bluetooth-connected devices,
and all other electronic devices must be identified and handed over to the
person proctoring the exam. Breaking the rules can result in expulsion. Each
student is required to make a copy of this paragraph, sign it indicating that
the contents are understood, and turn it in to John Reif.
Grading:
There
will be no make-up exams for missed exams. Missing one of the three
midterm exams will result in the remaining midterms and final exam grades being
re-weighted appropriately. By University Policy, missing the Final exam results
in a grade X.
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