Syllabus

Tentative topics include:

1. Introduction to Computational Economics:
  i. Mechanism Design: VCG Auctions, Optimal Auctions.
  ii. Equilibria and Price of Anarchy.
  iii. Internet-related Games, e.g., Selfish Routing, Content-distribution games.

2. Distributed Computation for Massive Data Sets.
  i. Mapreduce framework: simple mapreduce algorithms.
  ii. Large-scale Graph Clustering: Spectral Clustering, Modularity-based Clustering, Random Walks. 
  iii. Other Large-scale Graph Algorithms: Pregel framework.

3. (Social) Networks:
 i. Structure of social networks: Examples, Common Properties.
 ii. Networks: Models for social networks: random graphs, Preferential Attachment.
 iii. Link analysis Algorithms: Web Crawling and Ranking (PageRank, HITS).
 iv. Spread of Influence, Marketing, and Word-of-Mouth Advertising over Social Networks.

4. Market Algorithms and Computational Advertising
  i. Sponsored Search Auctions (AdWord Auction) and Online Advertisement.
  ii. Online Ad Serving: Display Ads, Mobile Ads.
  iii. Bid Optimization for Sponsored Ad Auctions.
  iv. Contract-based Display Advertising.
  v. Ad Exchanges, TV ad auctions.

5. Other E-Commerce Market Applications
 i. Reputation Systems (e.g. Ebay), and Web SPAM.
 ii. Recommendation Systems: Algorithms to maximize relevance, coverage, diversity.
 iii. Prediction Markets and online Matching Markets.



Last modified: November 16, 2013