## Key information - Class Meetings: Mondays and Wednesdays. 9:30-10:45 AM, WWH Room 109. - Midterm Exam: **Monday, October 20th** in class - Final Exam: **Wednesday, December 17th 10:00AM - 11:50AM** - Instructor: **Oded Regev**; office hour: Wednesday 8:00-9:00 AM in 303 WWH ### Recitation: - Recitation 1 (section 002): **Wilson Nguyen** (wdn2016), Fridays 11:00 AM-12:15 PM, 31 Washington Pl (Silver Ctr) Room 414; office hour: Mondays 9:00-10:00 AM 60 Fifth Ave 500 - Recitation 2 (section 021): **Rama Krishna** (rk4312), Fridays 12:30 AM -1:45 PM, 60 Fifth Ave Room 150; office hour: Fridays 2:45-3:45PM in 60 Fifth Ave Room 420 - Recitation 3 (section 022): **Wilson Nguyen** (wdn2016), Fridays 2:00-3:15 PM, 31 Washington Pl (Silver Ctr) Room 401; office hour: Mondays 9:00-10:00 AM 60 Fifth Ave 500 ### Course Assistants: - **Peter Hall** - **Daji Landis** (dl5489) Email me with admin issues and put "Basic Algorithms" in the subject line ### Tutors: In-person tutoring will be held in 230 WWH unless otherwise specified. - **Sai Akilesh Venigalla**: - **Chaehyun Chung**: - **In-person**: Thursdays 11:30 AM - 5:30 PM - **Online**: Wednesdays 5:30 PM - 8:00 PM; Fridays 4:00 PM - 8:00 PM; Saturdays 5:30 PM - 8:00 PM - **Vignesh Shanmugasundaram**: - **Ritesh Ojha**: - As this is a large class, we ask that you first try to post all questions on [Campuswire](), and/or attend the tutoring sessions. Please email your recitation leader only as a last resort. The instructor will not be able to respond to emails. ## Overview Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, binary search trees, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques. We will try to cover most of chapters 1-4, 6-8, 12, 15, 16, 22-25, 30, 31, 34 of [CLRS]. ## Prerequisites Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) or Mathematics for Economics I (MATH-UA 211). Also at least one year of experience with a high-level language such as Python, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees). ## Resources - **Introduction to Algorithms, 4th Edition, by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Cliff Stein**, published by MIT Press. Our main textbook. - Algorithm Design by Jon Kleinberg and Eva Tardos, Published by Pearson. - [Lecture Slides](http://www.cs.princeton.edu/~wayne/kleinberg-tardos/pearson/) for Algorithm Design by Kevin Wayne, distributed by Pearson. ## Links To be updated shortly - [Brightspace]() - [Campuswire]() - [Gradescope]() ## Summary of lectures For a summary of the lecture material along with relevant textbook and other links, please refer to the Brightspace for a working schedule. ## Course Policies ### Homework There will be weekly homework assignments. We prefer homework submissions typeset in LaTeX (you might want to use the [Overleaf templates](https://www.overleaf.com/read/fkgbwqztpqyd#ae92ef)) or Word. You are encouraged to insert scanned figures or illustrations. Scanned handwritten submissions will only be graded if *neatly written and perfectly legible*. Honors questions will be graded, but will not affect your grade in any way. Submission is through Gradescope. ### Grading Tentative grade split is 25% homework, 25% midterm, and 50% final exam. ### Late Submission Policy Each student gets a total of 5 joker days for the entire semester for late submissions. Each individual homework can, however, be submitted at most 2 days late. In other words, a student may submit up to five of the assignments one day late each without penalty, or alternatively submit two homework assignments late by two days each and an additional one by one day late. Solutions will not be graded if they are submitted later than two days after the specified deadline or the total quota of five late days is exceeded. ### Academic Integrity Please review the departmental [academic integrity policy](http://www.cs.nyu.edu/web/Academic/Graduate/academic_integrity.html). ### Use of LLMs LLMs are useful tools. Students are encouraged to use them while being careful to check the information they provide and to not to rely on them too heavily. They are good for small, specific questions ('what is this latex error!?'). Do not use them to solve your homework for you, but they can be helpful, although occasionally misleading, for getting unstuck on tough questions. Recall we have many hours of (real life human) tutors available to help you in these circumstances too. Minor usage does not need to be acknowledged, but major usage should be mentioned on homework and probably avoided. ### Collaboration We strongly encourage you to discuss assignments with your peers. However, all work that you submit must be your own. You must list all discussions you had. You **should not** consult previous years' students, code, assignments, etc. You may help other students and groups on specific technical issues but you must acknowledge such interactions.