Time 
Tuesday, 14 October 
Wednesday, 15 October 
Thursday, 16 October 
09:0010:00 
Morning Invited Talks 

Heikki Mannila
Finding Total and Partial Orders from Data for Seriation

László Lovász
Some Mathematics behind Graph Property Testing

Imre Csiszár
On Iterative Algorithms with an Information Geometry Background

10:0010:15 
Coffee Break 
10:1511:30 
Boosting and Experts 
Inductive Inference 
Statistical Learning 

Alexey Chernov, Yuri Kalnishkan, Fedor Zhdanov, and Vladimir Vovk
Supermartingales in Prediction with Expert Advice
Gold Award Lecture
Mikhail Dashevskiy
Aggregating Algorithm for a Space of Analytic Functions
Junichi Moribe, Kohei Hatano, Eiji Takimoto, and Masayuki Takeda
Smooth Boosting for MarginBased Ranking

John Case and Samuel E. Moelius III
Optimal Language Learning
Sanjay Jain and Frank Stephan
Numberings Optimal for Learning
Steffen Lange, Samuel E. Moelius III, and Sandra Zilles
Learning with Temporary Memory

Corinna Cortes, Mehryar Mohri, Michael Riley, and Afshin Rostamizadeh
Sample Selection Bias Correction Theory
Mark Herbster
Exploiting ClusterStructure to Predict the Labeling of a Graph
Ohad Shamir, Sivan Sabato, and Naftali Tishby
Learning and Generalization with the Information Bottleneck

11:3011:40 
Short Break 
11:4012:30 
Active Learning and Queries 
Boosting and Experts 
Probability and Stochastic Processes 

Gábor Bartók, Csaba Szepesvári, and Sandra Zilles
Active Learning of GroupStructured Environments
Shlomo Hoory and Oded Margalit
Finding the Rare Cube

Indraneel Mukherjee and Robert E. Schapire
Learning with Continuous Experts Using Drifting Games
Manfred K. Warmuth, Karen A. Glocer, and S.V.N Vishwanathan
Entropy Regularized LPBoost

László Györfi and István Vajda
Growth Optimal Investment with Transaction Costs
Processes
Ronald Ortner
Online Regret Bounds for Markov Decision Processes with Deterministic
Transitions

12:3014:00 
Lunch Break 
14:0015:00 
Afternoon Invited Talks 


Tom Mitchell
Computational Models of Neural Representations in the Human Brain

Daniel A. Keim
Visual Analytics: Combining Automated Discovery with Interactive Visualizations

Adjorn

15:0015:10 
Short Break 

15:1016:50 
Inductive Inference 
Active Learning and Queries 


Leonor BecerraBonache, John Case, Sanjay Jain, and Frank Stephan
Iterative Learning of Simple External Contextual Languages
Matthew de Brecht and Akihiro Yamamoto
Topological Properties of Concept Spaces
John Case and Timo Kötzing
Dynamically Delayed Postdictive Completeness and Consistency in Learning
John Case and Timo Kötzing
Dynamic Modeling in Inductive Inference

Dana Angluin, James Aspnes, and Lev Reyzin
Optimally Learning Social Networks with Activations and Suppressions
András Antos, Varun Grover, and Csaba Szepesvári
Active Learning in MultiArmed Bandits
M. Arias and J.L. Balcázar
Query Learning and Certificates in Lattices
MariaFlorina Balcan and Avrim Blum
Clustering with Interactive Feedback


16:5017:10 
Coffee Break 

17:1018:50 
Statistical Learning 
Probability and Stochastic Processes 


Shivani Agarwal
Generalization Bounds for Some Ordinal Regression Algorithms
Stéphan Clémençon and Nicolas Vayatis
Approximation of the Optimal ROC Curve and a TreeBased Ranking Algorithm
Andreas Maurer and Massimiliano Pontil
A Uniform Lower Error Bound for Halfspace Learning
Andreas Maurer and Massimiliano Pontil
Generalization Bounds for KDimensional Coding Schemes in Hilbert Spaces

Alexey Chernov, Alexander Shen, Nikolai Vereshchagin, and Vladimir Vovk
OnLine Probability, Complexity and Randomness
Vladimir Vovk and Alexander Shen
Prequential Randomness
Daniil Ryabko
Some Sufficient Conditions on an Arbitrary Class of Stochastic
Processes for the Existence of a Predictor
Arthur Gretton and László Györfi
Nonparametric Independence Tests: Space Partitioning and Kernel Approaches


19:00 
Business Meeting 
Banquet 
