Meetings: MWF 9:05am–9:55am, Uris Hall G01, map
- Bobby Kleinberg, Gates Hall 317, email
office hour: Tuesday 1:15pm–2:15pm and Wednesday 10:15am–11:15am
This course develops techniques used in the design and analysis of algorithms, with an emphasis on problems arising in computing applications. Example applications are drawn from systems and networks, artificial intelligence, computer vision, data mining, and computational biology. This course covers four major algorithm design techniques (greedy algorithms, divide and conquer, dynamic programming, and network flow), computability theory focusing on undecidability, computational complexity focusing on NP-completeness, and algorithmic techniques for intractable problems, including identification of structured special cases, approximation algorithms, and local search heuristics.
The textbook for the course is Algorithm Design by Jon Kleinberg and Eva Tardos (available at Cornell Store). Although this book was designed for this course, there will be topics covered in lecture that are not in the text and there will be topics in the text that are not covered in lecture. You are responsible for topics covered in lecture and for any assigned reading in the text.
The following books are also useful references.
- T. Cormen, C. Leiserson, R. Rivest. Introduction to Algorithms.
- A. Aho, J. Hopcroft, J. Ullman. The Design and Analysis of Computer Algorithms.
- M. Garey and D. Johnson. Computers and Intractability.
- D. Kozen. The Design and Analysis of Algorithms.
The prerequisites for the course are, either having an A– or better in both CS 2800 and CS 2110, or having successfully completed all three of CS 2800, CS 2110, and CS 3110. We assume that everyone is familiar with the material in CS 2110, CS 3110, and CS 2800, and we will use it as necessary in CS 4820. This includes elementary data structures, sorting, and basic terminology involving graphs (including the concepts of depth-first search and breadth-first search), and coding in Java. Some of these are reviewed in the text. The lectures and homework involve the analysis of algorithms at a fairly mathematical level. A few of the homework exercises consist of writing code in Java. We expect everyone to be comfortable reading and writing proofs at the level of CS 2800, as well as writing code in Java.
Your grade will based on weekly homework, two prelims, and one final exam. Each of these components will be given a weight in the following ranges:
- homework: from 15% to 25%
- prelim 1: from 15% to 25%
- prelim 2: from 15% to 25%
- final exam: from 25% to 40%
We will be using Piazza as an online discussion forum. Piazza allows for open discussions of all course-related questions. You are encouraged to post any questions you might have about the course material. The course staff monitor Piazza closely and you will usually get a quick response. If you know the answer to a question, you are encouraged to post it.
By default, your posts are visible to the course staff and other students, and you should prefer this mode so that others can benefit from your question and the answer. However, you can post privately so that only the course staff can see your question, and you should do so if your post might reveal information about a solution to a homework problem. You can also post anonymously if you wish. If you post privately, we reserve the right to make your question public if we think the class will benefit.
Everyone who preregistered for the course should already be signed up. If you have never used Piazza before, or if you did not preregister for the course, visit the Piazza CS 4820 page to sign up.
Piazza is the most effective way to communicate with course staff. Please avoid email if Piazza will do. Broadcast messages from the course staff to students will be sent using Piazza and all course announcements will be posted there, so check in often!
Homework is an important part of the course. We will have weekly homework assignments. All homework assignments will be posted on CMS. Most homework assignments will be due on Thursday at 11:59pm.
We recommend that your homework submissions are typeset, but this is not a requirement. In general, we recommend that you first develop your solutions in draft form, and then write or type your solution in a concise way. Typesetting forces you to do this last step (instead of handing in solution in draft form), which is why it is recommended. See typesetting resources for a list of typesetting software and references.
You have six late days. Late submission are graded only if you use your late days. You can use at most three late days per homework. The number of late days used on an assignment will be computed by taking the time interval between the deadline and the submission and rounding up to the nearest whole number of days. The purpose of the late days is to provide you with a buffer for dealing with unforeseen circumstances that may arise during the semester, including minor illnesses, injuries, traveling with a club or sports team, etc. In extreme cases of extenuating circumstances (long-term debilitating illness, family emergency, death of a family member or close friend), contact an instructor to make alternative arrangements.
You can collaborate with other students in the course and exchange ideas about homework. However, you are not allowed to share written notes about homework in any form. In particular, you need to write up your homework submission completely on your own. Your submission has to acknowledge all students that you collaborated with on the homework. Failure to acknowledge collaborators is a violation of academic integrity.
For the homework, it is not admissible to use resources beyond course material and student discussions. In particular, you may not use Wikipedia, or search the Web, or look at any textbook, other than the one assigned in the course. Using such additional resources is a violation of academic integrity.
- greedy algorithms
- dynamic programming
- network flow
- computability theory
- approximation algorithms
- randomized algorithms
Course Material Copyright
Course materials posted on this website, piazza, or CMS, are intellectual property belonging to the author. Students are not permitted to buy or sell any course materials without the express permission of the instructor. Such unauthorized behavior constitutes academic misconduct.
Any violation of academic integrity will be severely penalized. You are allowed to collaborate on the homework to the extent of formulating ideas as a group. However, you are expected to write up (and understand) the homework on your own, and you should acknowledge the names of the students with whom you collaborated.
Absolute integrity is expected of every Cornell student in all academic undertakings. Integrity entails a firm adherence to a set of values, and the values most essential to an academic community are grounded on the concept of honesty with respect to the intellectual efforts of oneself and others. Academic integrity is expected not only in formal coursework situations, but in all University relationships and interactions connected to the educational process, including the use of University resources. […]
A Cornell student's submission of work for academic credit indicates that the work is the student's own. All outside assistance should be acknowledged, and the student's academic position truthfully reported at all times. In addition, Cornell students have a right to expect academic integrity from each of their peers.