| Time |
Tuesday, 14 October |
Wednesday, 15 October |
Thursday, 16 October |
| 09:00-10:00 |
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
|
| 10:00-10:15 |
Coffee Break |
| 10:15-11:30 |
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
Jun-ichi Moribe, Kohei Hatano, Eiji Takimoto, and Masayuki Takeda
Smooth Boosting for Margin-Based 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 Cluster-Structure to Predict the Labeling of a Graph
Ohad Shamir, Sivan Sabato, and Naftali Tishby
Learning and Generalization with the Information Bottleneck
|
| 11:30-11:40 |
Short Break |
| 11:40-12:30 |
Active Learning and Queries |
Boosting and Experts |
Probability and Stochastic Processes |
|
Gábor Bartók, Csaba Szepesvári, and Sandra Zilles
Active Learning of Group-Structured 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
|
| 12:30-14:00 |
Lunch Break |
| 14:00-15:00 |
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
|
| 15:00-15:10 |
Short Break |
|
| 15:10-16:50 |
Inductive Inference |
Active Learning and Queries |
|
|
Leonor Becerra-Bonache, 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 Multi-Armed Bandits
M. Arias and J.L. Balcázar
Query Learning and Certificates in Lattices
Maria-Florina Balcan and Avrim Blum
Clustering with Interactive Feedback
|
|
| 16:50-17:10 |
Coffee Break |
|
| 17:10-18:50 |
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 Tree-Based Ranking Algorithm
Andreas Maurer and Massimiliano Pontil
A Uniform Lower Error Bound for Half-space Learning
Andreas Maurer and Massimiliano Pontil
Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces
|
Alexey Chernov, Alexander Shen, Nikolai Vereshchagin, and Vladimir Vovk
On-Line 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 |
|
