The 19th International Conference
Algorithmic Learning Theory

Hotel Budapest, Budapest, Hungary
October 13 - 16, 2008

Time Schedule

The conference starts on Monday, October 13th, with two tutorials and a Welcome Reception, scheduled as follows:

  • 13:30-15:30: Tutorial 1
    Saso Dzeroski: Constraint-Based Data Mining and Inductive Queries
  • 15:30-16:00: Coffee Break
  • 16:00-18:00: Tutorial 2
    João Gama: Mining from Data Streams: Issues and Challenges
  • 18:30: Welcome Reception
  • 18:30-20:00: Steering Committee Meeting

The table below presents the schedule for the other three days of the conference. Note that further info about the invited lectures can be found on the Invited Speakers page.

You may also take a look at the DS 2008 Program.

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
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

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