CS4800: Algorithms & Data

Syllabus

Schedule

Time & Location:

9:50 - 11:30am, TF, 104 West Village G

Staff

Instructor: Jonathan Ullman
    Office: 623 ISEC
    Office Hours: T 1:30-3:00pm

Teaching Assistant: Vikrant Singhal
    Office Hours: Th 4:00 - 6:00pm
    Location: 605 ISEC

Teaching Assistant: Konstantin Gizdarski
    Office Hours: W 5:00 - 7:00pm (Note the Change!)
    Location: WVH Atrium

Important Links

Piazza: https://piazza.com/ccs.neu.edu/spring2018/cs4800/home
Gradescope (Entry Code: MV8J4R): https://gradescope.com/

Overview

This is an introductory course in algorithms. Although any computer program can be viewed as an implementation of an algorithm for solving a particular computational problem, in this course we focus not on the programs themselves but on the underlying computational problems, and general algorithmic techniques for solving these problems. In this course, we will:

• See a wide range of computational problems arising in different applications
• Learn how to formulate these problems precisely from somewhat informal descriptions
• Learn new algorithmic design techniques used to solve these computational problems
• Learn techniques to prove correctness of algorithms
• Learn techniques to analyze the efficiency of algorithms
• Learn how to transform algorithms to programs

Discussion Forum: Piazza

We will be using Piazza for class discussion. The system will make it possible to get help quickly and and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I strongly encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com.

Please use this link to sign up for Piazza.

Textbook

Reading will be assigned mainly from

• Algorithm Design by Kleinberg and Tardos

Even though selling textbooks put me through college, I feel quite guilty about making students purchase expensive textbooks. If obtaining a copy is burdensome, please see me and I can lend you a copy for the semester.

You may find them useful as a reference or as an alternative perspective on some of the material, but they are not required:

• Algorithms, Etc. by Jeff Erickson
• Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein
• Mathematics for Computer Science by Lehman, Leighton, and Meyer

Homework Policies

All homework will be submitted through Gradescope as a PDF.

All homework solutions must be typeset in LaTeX. I will provide the source files for the HW assignments to help you get started. See below for some advice on LaTeX.

I encourage you to work with your classmates on the homework problems. If you do collaborate, you must write all solutions by yourself, in your own words, and are strictly forbidden from sharing any written solutions. You must list all of your collaborators on your submission. The TAs and I reserve the right to ask you explain your solutions.

No late homework will be accepted. Extensions will be granted only in rare, extreme, and verifiable circumstances. The lowest homework score will be dropped from your grade, so if you know that you wont be able to get a certain assignment in, plan ahead to take advantage of this policy.

Grading

The final course grade will be computed based on a weighted average of:

• homework (50%)
• two midterms (15% each)
• final exam (20%)

LaTeX

Learning LaTeX can take some time, but is well worth the investment, since most technical publications are written in LaTeX. Great editors exist on most platforms. Some recomend TexShop for Mac. TeXstudio is a good cross-platform editor. The not so short introduction to LaTeX is a good reference to get you started.