Monday, June 2, 2003
The Principle of Minimum Description Length
8:15 - 8:50 Breakfast and Registration
8:50 - 9:00 Opening Remarks
Melvin Janowitz, Associate Director of DIMACS
9:00 - 9:45 The MDL Principle with Distortion
Jorma Rissanen, Helsinki Institute for Information Technology
9:45 - 10:30 MDL and classification, revisited
Peter Grunwald, CWI Amsterdam
10:30 - 11:00 Break
11:00 - 11:45 Exact minimax estimation and MDL
Feng Liang, Duke University
11:45 - 12:05 Discussant
Paul Vitanyi, CWI and the University of Amsterdam
12:05 - 1:30 Lunch
Information Theory/Individual Sequences
1:30 - 2:15 On the lower limits of entropy estimation
Abraham Wyner and Dean Foster, University of Pennsylvania
2:15 - 3:00 Descriptions of words over a partially commutative alphabet
Serap Savari, Bell Laboratories, Lucent Technologies
3:00 - 3:45 Universal discrete Denoising: Known Channel
Marcelo Weinberger, Hewlett-Packard Laboratories
3:45 - 4:00 Break
Contributed Presentations
4:00 - 4:20 Redundancy of universal coding, Kolmogorov complexity
and Hausdorff dimension
Hayato Takahashi, Tokyo Institute of Technology
4:20 - 4:40 A new universal two part code for estimation of string Kolmogorov
complexity and algorithmic minimum sufficient statistics
Scott Evans, General Electric Research/RPI
4:40 - 5:00 Finite memory universal coding of individual binary sequences
Eado Meron, Tel Aviv University
5:00 - 5:20 Complexity preserving functions
Jan Lemeire, Vrije Universiteit Brussel
5:20 - 5:40 Some analysis of a predictive lossless coder for audio signals
Peng Zhao, University of California, Berkeley
Tuesday, June 3, 2003
Statistics and Learning
8:30 - 9:00 Breakfast and Registration
9:00 - 9:45 Data density and degrees of freedom in statistical models
Andrew Gelman, Columbia University and Mark Hansen, UCLA
9:45 - 10:30 Conditional Akaike Information for Mixed Effects Models
Florin Vaida, Harvard University
10:30 - 11:00 Break
11:00 - 11:45 Prequential Statistics and On-Line Learning
Phil Dawid, University College, London
11:45 - 12:30 Hierarchical Designs for Pattern Recognition
Donald Geman, Johns Hopkins University
12:30 - 2:00 Lunch
2:00 - 2:45 A General System for Incremental Machine Learning
Ray Solomonoff, Oxbridge Research
2:45 - 3:30 Boosting: convergence, consistency, and minimax results
Bin Yu, UC Berkeley
3:30 - 4:15 Date-dependent generalization bounds for
Bayesian mixture algorithms
Ron Meir, Technion
4:15 - 4:40 Break
Contributed Presentations
4:40 - 5:00 Message length estimators, probabilistic sampling
and optimal prediction
Ian Davidson, SUNY Albany
5:00 - 5:20 Data compression and learning
John Langford, IBM, TJ Watson
5:20 - 5:40 Classification or regression trees
Clayton Scott, Rice University
5:40 - 6:00 Learnability Beyond AC^0
Adam Klivans and Rocco Servedio, Harvard University
Wednesday, June 4, 2003
Cognitive Science
8:30 - 9:00 Breakfast and Registration
9:00 - 9:45 Incomputable randomness or computable regularity?
Peter A. van der Helm, Nijmegen Institute for Cognition and Information
9:45 - 10:30 Articulation and Intelligibility
Jont Allen, UIUC
10:30 - 11:00 Break
11:00 - 11:45 Science, Simplicity and Embodied Cognition
Nick Chater, University of Warwick
11:45 - 12:30 William Bialek
12:30 - 2:00 Lunch
Applications
2:00 - 2:45 Individual Sequence Properties of Compounded Wealth, Portfolio
Estimation, Option Pricing, and Model Selection
Andrew Barron, Yale University
2:45 - 3:30 Similarity metric and algorithmic music clustering
Paul Vitanyi, CWI and the University of Amsterdam
3:30 - 4:00 Break
Contributed Presentations
4:00 - 4:20 Subjective randomness and cognitive complexity
Tom Griffiths, Stanford University
4:20 - 4:40 Minimum description length cognitive modeling
Yong Su, Ohio State University
4:40 - 5:00 Using polynomial local search and Kolmogoro complexities
to better understand evolutionary algorithms
Natalio Krasnogor, University of Nottingham
5:00 - 5:20 Condensation of boolean formulas
Kazuo Iwama, Kyoto University
5:20 - 5:40 Complexity and vulnerability analysis
Stephen Bush, General Electric, Research
Thursday, June 5, 2003
K-complexity
8:30 - 9:00 Breakfast and Registration
9:00 - 9:45 Complexity Distortion Theory
Alex Eleftheriadis, Columbia University
Daby Sow, IBM T. J. Watson Research Center
9:45 - 10:30 Predictive complexity, randomness and information
Volodya Vovk
10:30 - 11:00 Break
11:00 - 11:45 Computational Depth
Lance Fortnow, NEC Laboratories America
11:45 - 12:30 Uniform randomness test, over a general space
Peter Gacs, Boston University
12:30 - 2:00 Lunch
2:00 - 2:45 The Kolmogorov Sampler
David Donoho
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