IIIS, Tsinghua University
Algorithms 2021 Fall
Instructor: Jian Li ( lapordge@gmail.com )
TA: Zeren Tan (tanzr20@mails.tsinghua.edu.cn), Hongxun Wu (wuhx18@mails.tsinghua.edu.cn), Qianfan Zhang (zqf18@mails.tsinghua.edu.cn)
Time: Every Monday Morning (9:50-12:15)
Classroom: 6A 117
Overivew:
This is a first course in design and analysis of algorithms
for undergraduate students. The main focus is about
some fundamental algorithmic techniques, such as greedy,
divide and conquer, dynamic programming and so on,
some fundamental combinatorial objects, such as graphs,
network flows, strings and so on,
and various mathematical tools to analyze them.
In the later part of the course, I will touch some
more advanced topics such as approximation algorithms
for NP-hard problems, randomized algorithms and so on.
The course forms a foundation for all areas of computer science.
We will discuss algorithmic problems from a variety of areas
such as AI, computational biology, networking and so on.
I will teach basic algorithmic concepts and techniques
in class, followed by some simple applications.
More advanced applications will be delivered in the
homeworks which form an important part of the course
and contribute to 30% of the final grade. We will also
have both the mid-term exam and the final exam, contributing
30% and 40% to the final grade, respectively.
Textbook£ºAlgorithm Design, by Jon Kleinberg and Eva Tardos. (You should be able to find it in Taobao also.)
We will use some homework problems from this book.
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Homeworks will be uploaded to Xuetang each week (usually before Wed).
The deadline is Wed of the next week. (so you have 1 week).
We will deduct 20% for a late hw for each day after the deadline (e.g., if you are 2 days late, we will subtract 40%£©
For bonus problems, you have two weeks.
For research problems, you have the whole semester.
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Mid term: TBA, in class. Scope: week 1-8
Final exam: TBA (in the exam week). Scope: things covered during the entire semester
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Other
Refs£º
[1] Introduction to Algorithms, 3rd edition (CLRS)
By Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
[2] Approximation Algorithms
By Vijay V. Vazirani
[3] Randomized Algorithms
Rajeev Motwani, Prabhakar Raghavan
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