Archive for DIMACS workshop on Online Decision Algorithms

The goal of this web page is to archive documents from the DIMACS meeting on Online Decision Algorithms that took place during July 12 to July 15, 1999 in Rutgers University in New Jersey.

The order to the items corresponds to the chronological order in which the talks were given. I have the slides for some of the talks. In addition, I put some reference lists, pointers to home-pages and pointers to papers that are available electronically. Some of the slides were handwritten, so I had to scan them in. Those slides appear in the adobe acrobat format (pdf) and are rather large. The electronically generated slides are in postscript format.

There are many missing items. If you have taken part in the workshop and would like to contribute additional slides or other material, please Email it to me at yoav@research.att.com.

A similar workshop was held in the University of California in Santa Cruz in 1996. Some papers and slides were saved from that meeting. You can access that archive by clicking here

Best Regards
Yoav Freund

Monday July 12, 1999

1. A short guided tour in the land of online decision algorithms
   Yoav Freund, AT&T Labs-Research
   Slides
   Home page

2. Learning in Games
   Rakesh Vohra, Northwestern University
   Slides
   Home page

3. An overview of the competitive analysis of online algorithms and its relation to game theory
   Allan Borodin, University of Toronto and Ran El-Yaniv, The Technion, Israel
   Slides
   Borodin's Home page
   El-Yaniv's Home page

4. The Prequential Approach to Probability and Statistics
   Philip Dawid, University College London
   Slides (Handwritten 3Mb pdf)

5. Decision Theory of Regret for Universal Coding, Gambling, and Prediction
   Andrew Barron, Yale University

6. Reinforcement learning as a useful apporximation: accuracy of prediction in experimental games.
   Alvin Roth, Harvard University
   Home page
    

   Tuesday July 13, 1999

7. Adaptive Srategies, Regret, and Approachability
   Sergiu Hart, Hebrew University, Jerusalem
   Paper: A General Class of Adaptive Strategies
   Paper: A Simple Adaptive Procedure Leading to Correlated Equilibrium
   Home page

8. Information Geometry and its Applications
   Imre Csiszar, Hungarian Academy of Sciences
   Slides (handwritten - 1.6Mb pdf)
   Reference list

9. Relative Loss Bounds for On-Line Learning Using Divergence Measures
   Manfred Warmuth, University of California - Santa Cruz
   Slides
   Home page

10. Learning to Play Games Using Multiplicative Weights
    Robert Schapire, AT&T Labs
    Slides
    Paper:Adaptive game playing using multiplicative weights
    Paper: Gambling in a rigged casino: The adversarial multi-armed bandit problem
    Home page

11. Worst-case analyses of the exploration/exploitation tradeoff
    Phil Long, National University of Singapore
    Slides
    Reference List
    Home page

12. Tracking the Best Predictor
    Mark Herbster, Royal Holloway University
    Slides

    Wednesday July 14, 1999

13. Rational Learning
    Ehud Kalai, Northwestern University
    Slides (handwritten 3.5 Mb pdf)
    Home page

14. Rational Bayesian Learning in Repeated Games
    John Nachbar, Wash University, St. Louis

15. "When rational learning fails"
    Dean Foster, Wharton School, University of Pennsylvania and Peyton Young,
    John Hopkins University

16. `Impossibility' of Absolute Continuity
    Chris Sanchirrico, Columbia University

17. Minimizing regret: the general case
    Aldo Rustichini, Tilburg University

18. Reasonable Learning in Non-cooperative Games and the Internet
    Eric Friedman, Rutgers University, Department of Economics
    Slides
    Home page

19. Bayesian representations of stochastic processes under learning - De-Finetti revisited
    Matt Jackson, CalTech; Rann Smorodnitsky, Technion, and Ehud Kalai, Northwestern University
    Papers

20. Fast Universal Portfolios For Parameterized Target Classes
    Jason Cross, Yale University

21. On-Line Learning and the Metrical Task System Problem
    Avrim Blum, Carnegie Mellon University
    Slides
    Associated Paper: Avrim Blum and Carl Burch, On-line Learning and the Metrical Task System Problem.
    Proceedings of the 10th Annual Conference on Computational Learning Theory (COLT '97), pages 45--53. To appear in Machine Learning.
    Home page

22. Choosing the best option under adversarial conditions
    Yossi Azar, Tel Aviv University
    Home page

23. On prediction of individual sequences relative to a set of experts.
    N. Cesa-Bianchi, University of Milan, Italy and Gabor Lugosi,
    Pompeu Fabra University, Spain
    Cesa-Bianchi's home page
    Lugosi's home page

24. Approachability in Infinite Dimensional Spaces and an Application:
    A Universal Algorithm for Generating Extended Normal Numbers
    Ehud Lehrer, Tel-Aviv University

25. Calibration with Many Checking Rules
    Alvaro Sandroni, Northwestern University

26. Average case and worst case sample complexity of learning distributions
    Manfred Opper, Sheffield University
    Slides
    Home page

    Document last modified on August 5, 1999.