CS 672: Computational Economics for Data Analytics

Course Information


Instructor: Yongfeng Zhang
Email: yongfeng.zhang AT rutgers.edu
Office: CoRE 309
Time: Monday and Wednesday, 5:00-6:20 pm
Location: Hill 116
Office Hours: Fridays 2:00-3:00pm or by appointment
TA: Yunqi Li
Email: yunqi.li@rutgers.edu

Announcements

  • 9/5: The first class is on Wednesday, Sep 5.

    • Course Descriptions

    The fundamental goal of the course would be to introduce how to integrate machine learning and economic principles in a variety of tasks, including but not limited to recommender systems, online advertising, sharing economy, social networks, etc, which covers many basic web-based services in Google, Facebook, Amazon, Microsoft, Uber, Airbnb, etc. The class will be a mixture of instructor lectures and student presentations.


    Prerequisites

  • CS 512 or CS 513 (Fundamental Algorithms)
  • CS 536 (Machine Learning) is preferred but not required
  • Linear Algebra, Basic Probability (Moments, Typical Distributions, MLE)
  • Programming Languages: C++/Java/Python/R

    • Expected Work

  • Paper Presentations: Complete as a team of at most 2 students (40%)
  • Final Project: Complete as a team of at most 2 students, choose between an assigned project or a self-proposed project, provide a presentation and complete a project report (60%)

    • Self-proposed projects are encouraged but are subject to pre-approval by the instructor.


    Tentative Schedule

    Note that the schedule may be subject to change (e.g., due to snow or campus close). Please check the course website frequently for the latest schedule.

    Week
    Date
    Topics and Assignments
    1
    9/5

    		   Introduction to Economics and Computation
    2
    9/10
    9/12

    		   Basics of Micro-Economics
      Basics of Game Theory
    3
    9/17
    9/19

    		   Basic Machine Learning
     Economics of Recommender Systems
    4
    9/24
    9/26

    		   Sponsered Search
      Online Advertising
    5
    10/1
    10/3

    		   Sharing Economy
      The Matching Market
    6
    10/8
    10/10

    		   Profit Maximization in Online Services (EC/Search/P2P)
      Profit Maximization in Online Services (Matching approaches)
    7
    10/15
    10/17

    		   Computational Advertising (Search Systems)
      Computational Advertising (Social Networks)
    8
    10/22
    10/24

    		   Matching in Sharing Economy
      Dynamic Pricing in Sharing Economy
    9
    10/29
    10/31

    		   Crowd sourcing
      Online Freelancing
    10
    11/5
    11/7

    		   Online Auction and Mechanism Design I
      Online Auction and Mechanism Design II
    11
    11/12
    11/14

    		   Fairness and Risk in Online Services I
      Fairness and Risk in Online Services II
    12
    11/19
    11/21

    		   Digital Marketplace and Summary
      Presentation of Projects
    13
    11/26
    11/28
     

    		   Presentation of Projects
      Presentation of Projects
    14
    12/3
    12/5

    		   Presentation of Projects
      Presentation of Projects
    15
    12/10
    12/12

    		   Presentation of Projects
      Presentation of Projects and Summary of the Class


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