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COMP9007 – Algorithms
Course page:
https://canvas.sydney.edu.au/courses/13954
Lecturer: Matloob Khushi
matloob.khushi@sydney.edu.au
Tutors: Paul Hunter, Darcy Townsend,
Samuel Isaac Arch, Anuj Dhavalikar,
Jaideep Singh
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Guidelines and tips
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Stable Matching Algorithm: A Comprehensive Guide with Examples, Lecture notes of Algorithms and Programming
[Week 1] Design and Analysis and Algorithms, Stable Match Making
Typology: Lecture notes
2018/2019
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1
COMP9007 – Algorithms
Course page:
https://canvas.sydney.edu.au/courses/
Lecturer: Matloob Khushi
[email protected]
Tutors: Paul Hunter, Darcy Townsend,
Samuel Isaac Arch, Anuj Dhavalikar,
Jaideep Singh
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Reference book: Algorithm Design by J. Kleinberg and E. Tardos Addison-Wesley
Introduction to Algorithms By Thomas H. Cormen Outline: 12 lectures 3 assignments 3 quizzes Final Exam
Tutorials:
12 tutorials (immediately after each lecture)
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Progressive Marks - 40% Quizzes 20% Assignments 20%
Final Exam - 60% (minimum 40% required to pass)
e.g. Progressive Mark = 80% Exam Mark = 50%
Final mark = (80 x 0.4 + 50 x 0.6) = 62
Assessment Summary
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Assessment Due Time/Date
Quiz 1 7:00PM Fri 22 March 2019 (Week 4) Assignment 1 11:00PM Fri 22 March 2019
Quiz 2 7:00PM Fri 12 April 2019 (Week 7) Assignment 2 11:00PM Fri 12 April 2019
Quiz 3 7:00PM Fri 24 May 2019 (Week 12) Assignment 3 11:00PM Fri 24 May 2019
Assessment Schedule
Final exam
› The final will be 2.5 hours long. It will consist of 6 problems
similar to those seen in the tutorials and assignments, plus one
challenge problem
› The final will test your problem solving skills
› There is a 40% exam barrier
› The final exam represents 6 0% of your final mark
› A student must also achieve an overall final mark of 50 or more
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› Introduction - Julián Mestre
Lectures & Tutorials
› Lecture 5:00 PM - 6:50 PM
› Lecture break / discussion Lecture
› Tutorial 7:00 PM – 8:0 PM
› We will post solutions to the tutorials.
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COMP9007: Algorithms
Algorithms then, and now
History
Wikipedia: The word 'algorithm' is a
combination of the Latin word algorismus,
named after Muhammad ibn Musa al-
Khwarizmi and the Greek word arithmos, i.e.
αριθμός, meaning "number".
Abacus
What's in an algorithm?
In 2003 there were examples of problems that we can solve 43 million times faster than in 1988
− This is because of better hardware and better algorithms
In 1988
− Intel 386 and 386SX
About 275,000 transistors clock speeds of 16MHz, 20MHz, 25MHz, and 33MHz − MSDOS 4.0 and windows 2.
− VGA
In 2003
− Pentium M
About 140 million transistors Up to 2.2 GHz − AMD Athlon 64
− Windows XP
What's in an algorithm?
In 2003 there were examples of problems that we can solve 43 million times faster than in 1988
− This is because of better hardware and better algorithms
Efficient algorithms produce results within available resource limits
In practice
− Low polynomial time algorithms behave well
− Exponential running times are infeasible except for very small instances, or carefully designed algorithms
Performance depends on many obvious factors
− Hardware − Software − Algorithm − Implementation of the algorithm
This unit: Algorithms
Efficient algorithms
Efficient algorithms “do the job” the way you want them to...
− Do you need the exact solution?
− Are you dealing with some special case and not with a general problem?
− Is it ok if you miss the right solution sometimes?
Efficient algorithms
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Chapter 1
Introduction:
Some Representative
Problems
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A First Problem: Stable Matching
Goal. Given a set of preferences among hospitals and medical school
students, design a self-enforcing admissions process.
› Unstable pair: applicant x and hospital y are unstable if:
- x prefers y to its assigned hospital.
- y prefers x to one of its admitted students.
› Stable assignment. Assignment with no unstable pairs.
- Natural and desirable condition.
- Individual self-interest will prevent any applicant/hospital deal from being made.