Algorithms & Economics of the Internet, CSCI-GA.3033-003

main web page for the course.

Instructors. Vahab Mirrokni (Google Research) and Richard Cole (NYU)
Contact info:;, 417 WWH, tel: 998-3119.
Instructional Assistant. Long Yang,

Class time. 5:10-7:00pm, Thursday, room 202 WWH.
First meeting.  Thursday, January 30.

Course Description We will be studying algorithmic and economic problems related to Internet search, online advertizing, social networks, and online markets. We will discuss important economic aspects: the ideas behind Internet ad auctions, and the game theoretic analysis of self-interested agents interacting over the Internet. We will also cover the central algorithmic ideas behind the large-scale analysis of the huge data sets supporting Internet search. Our goal is to obtain a rigorous understanding of the properties of such environments and to explore these properties to solve the data mining and optimization problems emerging in these environments. The main areas include computational economics, computational advertising, (social) network analysis, commerce applications, and large-scale distributed computation.


Prerequisites. Fundamental Algorithms or a similar algorithms course; Mathematical Techniques For CS Applications, or knowledge of linear algebra and discrete probability.

Assessment. Homework 40%; reading from the literature with brief written reports 10%; final project: this will likely be an implementation project, but could also be a survey paper or even a research paper; all groups will make a 5-10 minute presentation at the final class session.

Academic Integrity.  Please take note of  the course and departmental policy on this matter:

Required text. None.


Homework 1
Homework 2
Homework 2 addendum
Homework 3
Homework 4
Homework 5
Homework 6
Homework 7
Homework 8
Homework 9
Homework 10

S. Brin, L. Page, The Anatomy of a HyperTextual Web Search Engine, WWW 1998.
R. Andersen, C. Borgs, J. Chayes, J. Hopcroft, K. Jain, V. Mirrokni, S. Teng, Robust PageRank and Locally Computable Spam Detection Features, AIRWeb 2008.

Last modified: April 17, 2014