Spring 2011: Light Seminar on Machine Learning (16:198:500:01)

1 credit

Instructors: Tina Eliassi-Rad and Michael Littman

Date/Time: Wednesdays from 11 AM to 12:30 PM

Place: CoRE 301

Description: In the era of big data, machine learning is ubiquitous. This light seminar will explore state-of-the-art research in machine learning and its applications in various domains. Each week, we will either listen to an invited speaker (from the Rutgers-Yahoo! Machine Learning Seminar) or discuss selected articles.

Grading: Grades for this seminar will be based on upon paper presentation and class participation.


Date Agenda Speaker
January 19 Efficient Bayesian Methods for Hierarchical Clustering Katherine A. Heller
January 26 Topic Models We Can Believe In: New Approaches to Evaluating Latent Variable Models for Text Analysis David Mimno
February 2 Discuss:
  • E. Keogh. How to do good research, get it published in SIGKDD and get it cited!
    Tutorial at The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009.
    Presentation is available at our Sakai site.
  • ---
    February 9 Discuss:
  • V. Chandola, A. Banerjee, V. Kumar. Anomaly detection: A survey. ACM Computing Surverys 41(3), 2009.
  • ---
    February 16 Discuss:
  • A. Halevy, P. Norvig, F. Pereira. The unreasonable effectiveness of data. IEEE Intelligent Systems, 2009.
  • E. Wigner. The unreasonable effectiveness of mathematics in the natural sciences. Communications of Pure and Applied Mathematics 13(1), 1960, pp. 1-14.
  • ---
    February 23 Machine Learning Algorithms for Real Data Sources, with Applications to Climate Science Claire Monteleoni
    March 2
    Location: CoRE Auditorium (Room 101)
    Learning Feature Hierarchies for Vision Yann LeCun
    March 9 Comprehensive Patient Similarity Learning Jimeng Sun
    March 16 Spring Break ---
    March 23 Inferring the Structure and Scale of Modular Networks Jake Hofman
    March 30 Socially Intelligent Machine Learning Haym Hirsh
    April 6 Collective Graph Identification Lise Getoor
    April 13 Some Remarks on the Model Selection Problem Branden Fitelson
    April 20 How ML Relates Victoria Stilwell to George Lucas David L. Roberts
    April 27 Computational Insights into Population Biology Tanya Berger-Wolf
    May 4 Recommender Systems: The Art and Science of Matching Items to Users Deepak Agarwal

    Related site: Rutgers-Yahoo! Machine Learning Seminar