8:30 - 9:00

Conference Opening, by Marty Golumbic, General Chair, and Frederick Hoffman, Conference Chair

Learning I

Satisfiability (invited session)

9:00

E. Harris: Information Gain Versus Gain Ratio: A Study of Split Method Biases

John Franco: A Non-linear SAT Solver

9:30

B. Apolloni, D. Malchiodi: Narrowing confidence interval width of PAC learning risk function by algorithmic inference

Bert Randerath: On satisfiable CNF-formulas closed under literal flipping

10:00

L.E. Raileanu, K. Stoffel: Theoretical Comparison between the Gini Index and Information Gain Criteria

Ewald Speckenmayer: Worst case bounds for XSAT and Set Partitioning

Learning II

Graphs and Numbers

11:00

J.P. Bernick: Minimizing Output Error in Multi-Layer Perceptrons

S. Colton, L. Dennis: The NumbersWithNames Program

11:30

M. Nakamura and K. Uehara: Improvement of Boosting Algorithm by Modifying the Weighting Rule

T. Dimitriou: Characterizing the Space of all Cliques in Random Graphs using ``Go with the Winners''

12:00

S.K.M. Wong, T. Lin, D. Wu: Construction of a Bayesian DAG from Conditional Independencies

E. Byeon: Graph decomposition heuristic for machine scheduling problems

Learning III

Confidence machines, POMDPS

11:00

M. Hermo, V. Lavin: Negative Results on Learning Dependencies with Queries

H. Papadopoulos, K. Proedrou, V. Vovk, A. Gammerman: Inductive Confidence Machines for Regression

11:30

M. Tsuyuguchi, K. Uehara: Bias-Variance-Decomposition of Zero-One Loss in Average-Case Model

K. Proedrou, I. Nouretdinov, V. Vovk, A. Gammerman: Transductive Confidence Machines for Pattern Recognition

12:00

E.N. Smirnov, H.J. van den Herik, I.G. Sprinkhuizen-Kuyper: Adaptable Boundary Sets

W. Zhang, N.L. Zhang: An Alternative Formulation of Dynamic-Programming Updatesfor POMDPs

16:00 - 17:00 Plenary lecture: INVITED TALK I

Searching in the Space of Very Large Structured Models