The 20th International Conference
Algorithmic Learning Theory

University of Porto, Portugal
October 3 - 5, 2009

Time Schedule

The conference starts on Friday, October 2nd, with a Welcome Reception from 19:00 - 21:00.

The registration desk is open every morning starting at 8:00. So, please come there in the morning to register.

On Saturday, October 3rd, we start with the following two tutorials scheduled as follows:

  • 08:30-10:30: Tutorial 1
    Concha Bielza and Pedro Larrañaga : Computational Intelligence for Neuroscience
  • 10:30-11:00: Coffee Break
  • 11:00-13:00: Tutorial 2
    Howard J. Hamilton and Fabrice Guillet : Interestingness Measures for Knowledge Discovery

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 2009 Program.

Time Saturday, 3 October Sunday, 4 October Monday, 5 October
09:00-10:00 Tutorial Morning Invited Talks
Concha Bielza and Pedro Larrañaga
Computational Intelligence for Neuroscience
Yishay Mansour
Learning and Domain Adaptation
Jiawei Han
Mining Heterogeneous Information Networks By Exploring the Power of Links
10:00-10:15 Coffee Break
10:15-10:45 DS 2009: Carl Smith
Award Paper
ALT 2009: E. Mark Gold Award Paper

Nader Bshouty and Hanna Mazzawi
Reconstructing Weighted Graphs with Minimal Query Complexity
10:45-11:00 Coffee Break
11:00-12:40 Tutorial Inductive Inference I Active Learning and Query Learning
Howard J. Hamilton and Fabrice Guillet
Interestingness Measures for Knowledge Discovery
(note that this tutorial finishes at 13:00)

John Case and Timo Koetzing
Difficulties in Forcing Fairness of Polynomial Time Inductive Inference

Ryo Yoshinaka
Learning Mildly Context-Sensitive Languages with Multidimensional Substitutability from Positive Data

Sanjay Jain, Pavel Semukhin, Qinglong Luo, and Frank Stephan
Uncountable Automatic Classes and Learning

Sanjay Jain, Frank Stephan, and Nan Ye
Learning from Streams
Andrew Guillory and Jeff Bilmes
Average-Case Active Learning with Costs

Marta Arias and José Luis Balcázar
Canonical Horn Representations and Query Learning

Balázs Szörényi

Characterizing Statistical Query Learning: Simplified Notions and Proofs

Ricard Gavaldà and Denis Thérien
An Algebraic Perspective on Boolean Function Learning
13:00-14:00 Lunch Break
14:00-15:00 Afternoon Invited Talks
Hector Geffner
Inference and Learning in Planning
Fernando C.N. Pereira
Learning on the Web
Sanjoy Dasgupta
The Two Faces of Active Learning
15:00-15:10 Short Break
15:10-16:25 Online Learning I Learning Graphs and Automata Semi-Supervised and Unsupervised Learning
Alexey Chernov and Vladimir Vovk
Prediction with Expert Evaluators' Advice

Sebastien Bubeck, Remi Munos, and Gilles Stoltz
Pure Exploration in Multi-armed Bandits Problems

Vladimir V'yugin
The Follow Perturbed Leader Algorithm Protected from Unbounded One-Step Losses
Nicolò Cesa-Bianchi, Claudio Gentile, and Fabio Vitale
Learning Unknown Graphs

Tatsuya Akutsu, Takeyuki Tamura, and Katsuhisa Horimoto
Completing Networks Using Observed Data

Dana Angluin, Leonor Becerra-Bonache, Adrian Dediu, and Lev Reyzin
Learning Finite Automata Using Label Queries
Hans Simon
Smart PAC-Learners

Stefanie Jegelka, Suvrit Sra, and Arindam Banerjee
Approximation algorithms for tensor clustering

Maria Florina Balcan, Heiko Röglin, and Shang-Hua Teng
Agnostic Clustering
16:25-16:45 Coffee Break
16:45-18:00 Statistical Learning Online Learning II Inductive Inference II
Stéphan Clémençon and Nicolas Vayatis
Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm

Odalric-Ambrym Maillard and Nicolas Vayatis
Complexity versus Agreement for Many Views: Co-Regularization for Multi-View Semi-Supervised Learning

Alina Beygelzimer, John Langford, and Pradeep Ravikumar
Error-Correcting Tournaments

Łukasz Dębowski

Computable Bayesian Compression for Uniformly Discretizable Statistical Models

Vianney Perchet

Calibration and Internal No-Regret with Random Signals

László Györfi and Peter Kevei
St. Petersburg Portfolio Games
Sanjay Jain and Efim Kinber

Iterative Learning from Texts and Counterexamples Using Additional Information

Lorenzo Carlucci
Incremental Learning with Ordinal Bounded Example Memory
19:00- Business Meeting Banquet Farewell Party

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