Fall 2017 CS231
This is a course about algorithms and their analysis
The language of computer science is to a great extent the language of algorithms. Although there are many thousands of algorithms, there are relative few basic design techniques. These include: divide-and-conquer, greedy, dynamic programming, and network flow. We will illustrate these techniques by studying a few fundamental algorithms of each type. In addition to helping us understand classic solution techniques, these algorithms have proven very useful in practice. Their names and the names of the problems they solve have become a standard part of the language of computer science.
Unfortunately, there is rarely a best algorithm to solve a given problem. Each approach involves a series of tradeoffs. Therefore, we will also study methods for evaluating the usefulness of an algorithm in a given situation. Among the various competing measures, we will focus primarily on the anal- ysis of time and space complexity. However, a number of other issues will also be discussed.
Labor Day: no classes
Lecture 1: Introduction
Part I - Basics
Lecture 2: Tractability and Asymptotic order or growth
Lecture 3: The Stable Matching problem
Assignment 1 due at 9:00pm
Lecture 4: Priority Queues
Lecture 5: Priority Queues and Binary Search Trees
Assignment 2 due at 9:00pm
Part II - Graphs
Lecture 6: Intro and Basics
Lecture 7: Graph Traversals
Assignment 3 due at 9:00pm
Lecture 8: Connectivity in Graphs and Topological Ordering
Add your questions here
Fall Break: no classes
Fall Break: no classes
Part III - Greedy Algorithms
Lecture 9: Scheduling
Assignment 4 - Full version due at 9:00pm
Lecture 10: More on Scheduling
Lecture 11: Scheduling again?!
Assignment 5 due on Sunday at 11:59pm
Exam 1Includes: Everything until the end of Lecture 11
Part IV - Divide and Conquer
Lecture 13: Merge Sort
Lecture 14: Recurrence Relations and More on Sorts
Lecture 15: More on Divide and Conquer
Part V - Dynamic Programming
Lecture 16: Basics and Principles
Assignment 6 due at 9:00pm
Lecture 17: The Knapsack problem
Lecture 18: Back to Graphs :)
Assignment 7 due at 11:59pm
Exam 2 - In classIncludes: Everything till the end of lecture 18
Part VI - Advanced Topics
Lecture 19: Network Flow (1)
Lecture 20: Network Flow (2)
Lecture 21: Computational intractability and NP-Completeness
Lecture 22: A peek into distributed algorithms
Assignment 8 due at 9:00pm
Lecture 23: Final poster presentations
Last day of classes
Final Paper Due
Enjoy your break :)
Prerequisites The prerequisite for CS231 is CS230, and Math 225. Students with significant mathematical experience (writing and understanding proofs), or those who have not taken Math 225 need the permission of the instructor.
Textbook - Very Important!! The textbook for this semester is Regular readings will be assigned from the required text, Algorithm Design, by by Jon Kleinberg and Eva Tardos, 1st edition. It is required that you read the relevant sections every lecture.
Computers No programming will be done as part of this course. You will need your computers, however, to type your assignments. You are expected to use Latex for typesetting all assignments in this course.
Course Directory The CS231 course directory is located at /home/cs231 on tempest. You will be submitting your assignments, in pdf format, in that directory. Any required material, if any, of the course will be placed in the download folder inside the /home/cs231 directory, and you can access it using an ftp program (like Fetch on a Mac).
Please add yourself to the cs231-fall2017 google group. This group has several
purposes. We will use it to make class announcements, such as
corrections to assignments and clarifications of material discussed in
class. We encourage you to post questions or comments that are of
interest to students in the course.
The instructors and TAs will read messages posted in the group on a regular basis and post answers to questions found there. If you know the answer to a classmate's question, feel free to post a reply yourself. The course group is also a good place to find people to join a study group. You should plan on reading group messages on a regular basis.
Lectures There are two 70-minute lectures each week that will introduce the main content of the course. Lectures are held on Mondays and Thursdays at 9:50-11:00 AM (section 01 in SCI 104), and at 11:10AM-12:20PM (section 02 in SCI 104), and
Supplemental Instruction (SI) Supplemental Instruction (SI) is an academic support program offered for selected Wellesley courses. Our academic SI leaders, Elizabeth is trained and highly experienced in tutoring. She will offer two study sessions each week throughout the semester. During SI sessions they will cover problem set solutions and review important concepts. SI sessions are open to all students enrolled in the course. We highly recommend attending one of the SI sessions every week, as well as reviewing the handouts used in SI sessions.
Final Poster and Paper: During the last few weeks of the semester, teams of 2-3 students work on a short survey paper. After choosing an interesting algorithmic problem, you will first read related literature on the topic, and summarize your findings into a short scientific paper (3-4 pages). Each team will present their work in a poster session during the last class, and will prepare a short paper to be submitted by the last day of exams.
Exams: There will be two in-term, non-collaborative exams that are open book and open notes. The first is in-class and the other one might be take-home. There will be no final exam, as there will be a final poster and paper instead. You are not allowed to collaborate with anyone else on the take-home exams. The dates of the exams are listed on the schedule. Please mark the exam dates in your calendars as they are not flexible.
Final Grades Your final grade for the course will be computed as a weighted average of several components. The relative weight of each component is shown below:
Q: How can we memorize all of these algorithms before the exam?
A: The exam is open book / notes. No need to memorize anything.
Q: How long will the exam be?
A: It's only 70 minutes long. Definitely shorter than the assignments!
Q: How will the questions look like?
A: A mix of things, but it'll never be a type of problem, in which you write the algorithm to solve a new problem, and analyze it.
Q: If the problem doesn't ask us to prove the correctness of the algorithm, then we don't have to write a proof. Right?
A: Yes, you don't have to write a proof. However, what if your algorithm was incorrect? Showing us your reasoning would give you partial credit. Just a simple explanation of your reasoning would suffice.
Q: Should I write the algorithm in English? Or do I have to explain the data structures that I am using?
A: If you are not required to show the data structures that you'll be using, then you can just explain the algorithm in English. Remember, if you are asked to analyze the running time complexity of the algorithm, thinking about which data structures to use matter.
Q: Do I have to use the latex template provided?
A: No, you don't, but you have to type it in latex, and submit a pdf. If you don't use the same template, you must at least copy the header of the assignment, to fill in the assignment meta data.