CSCI-UA.0310-001 Basic Algorithms, Fall 2016

Lecturer: Prof. Yevgeniy Dodis, dodiscs.nyu.edu, (212) 998-3084, room 413, WWH. Office hour: Tuesday 6pm-7pm.
Meeting Time/Place: TR 3:30pm-4:45pm, room 109, WWH.
Recitation Time/Place: Wed 3:30pm-4:45pm, room 109, WWH.
Recitation Instructor: Sandro Coretti, Room 408, WWH.
Office hours: Monday 6pm-7pm in room 905; Thursday 5pm-6pm in room 605.
Midterm: Oct 25, 3.30pm-4:45pm, room 109.

Final: Thursday, December 22nd, 4pm-5.50pm, room 109.

Mailing list: To subscribe to the class list, follow instructions at
http://www.cs.nyu.edu/mailman/listinfo/csci_ua_0310_001_fa16
To post a message to all the list members, send email to csci_ua_0310_001_fa16@cs.nyu.edu. Please, post only messages interesting to everybody taking the class. Specific class-related questions and most of your other correspondence should be directed to the instructor.
Course Homepage: http://cs.nyu.edu/courses/fall16/CSCI-UA.0310-001/index.html
NYU classes (for homework submission): https://newclasses.nyu.edu/portal/site/096a3446-3455-48e3-90e6-8e24299d843a#

Lecture Summaries (see also Selected Notes from MIT)

Additional Handouts:

Problem Sets:


Brief Course Description:

This is an introductory course in algorithms. We will cover standard topics such as sorting, divide-and-conquer, various data structures, graph algorithms, dynamic programming, greedy algorithms, and - time permitting - online and approximation algorithms. The emphasis will be given to arguing the correctness of algorithms and performing the analysis of their running time.

Textbook:

Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Cliff Stein, published by MIT Press.
You can get either the THIRD EDITION (recommended) or the SECOND EDITION. The exercises will refer to the THIRD edition.

Grading:

There will be one in-class midterm and a final exam, in addition to approximately weekly homework assignments. Tentative grade split is 40% homework, 25% midterm and 35% final exam. Students on the "boundary" between two grades might increase their grade by doing accurate self-grading, as explained below.

Homework:

Each problem set will consist of several problems. Some of the homework exercises will be routine, but others will be more challenging. I do not expect you to solve all of the homework problems, but I hope that you will benefit from working on the more difficult ones. Homework will be assigned the day of the class, and will be due the following week (unless stated otherwise). No late homework will be accepted. The solutions will be discussed during the recitation immediately following the due date of the homework. We encourage the students to come to the recitation - not only for the homework solutions, - but primarily to see examples of the problems similar to those assigned for the following week.

The maximum point value for each problem (and, sometimes, parts of the problem) will be stated on the homework. Some questions in the homework will be for the extra credit, and will be explicitly marked as such (together with their maximum extra credit) on each assignment. Solving such problems can make your overall grade for the homework above 100%, or, alternatively, effectively "erase" the credit lost for not solving some of the required problems.

Self-Grading:

Another way where copying homework is useful is for self-grading. In particular, after the students handed in their homework and learned the correct solutions during the following recitation, but before getting back their graded solutions, the students can hand in their self-graded homework, using the same grading system they expect from the actual graders. Unlike regular homework, self-graded homework should only be submitted by email to the Recitation Instructor. We believe self-grading their own mistakes will greatly improve the students' understanding of the material. Moreover, as explained above, students on the "boundary" between two grades might increase their grade by doing accurate self-grading.

Concluding Remarks: