The 15th International Conference


The following papers have been accepted for ALT 2004. There is no particular order in the list. Please keep in mind that we need your final version until July 25, 2004.
Relative Loss Bounds and Polynomialtime Predictions for the KLMSNET Algorithm  Mark Herbster
 
On Kernels, Margins, and Lowdimensional Mappings

MariaFlorina Balcan, Avrim Blum, and Santosh Vempala  
Complexity of Pattern Classes and Lipschitz Property

Amiran Ambroladze and John ShaweTaylor  
Universal Convergence of Semimeasures on Individual Random Sequences 
Marcus Hutter and Andrej Muchnik  
On the Complexity of Working Set Selection 
Hans Ulrich Simon  
Learnability of Relatively Quantified Generalized Formulas  Andrei Bulatov, Hubie Chen, and Victor Dalmau  
Prediction with Expert Advice by Following the Perturbed Leader for General Weights

Marcus Hutter and Jan Poland  
Learning Languages from Positive Data and Negative Counterexamples 
Sanjay Jain and Efim Kinber  
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions  Keisuke Yamazaki and Sumio Watanabe 

A Criterion for the Existence of Predictive Complexity for Binary Games

Yuri Kalnishkan, Vladimir Vovk, and Michael V. Vyugin  
On the Convergence Speed of MDL Predictions for Bernoulli Sequences 
Jan Poland and Marcus Hutter  
Convergence of a Generalized Gradient Selection Approach for the Decomposition Method  Nikolas List


Comparison of Query Learning and Goldstyle Learning in Dependence of the Hypothesis Space 
Steffen Lange Sandra Zilles  
Learning of Ordered Tree Languages with HeightBounded Variables using Queries  Satoshi Matsumoto and Takayoshi Shoudai 

Learning rofk functions by Boosting 
Kohei Hatano and Osamu Watanabe  
Decision Trees: More Theoretical Justification for Practical Algorithms  Amos Fiat and Dmitry Pechyony 

Learning Languages generated by Elementary Formal Systems and its Application to SH Languages 
Yasuhito Mukouchi and Masako Sato  
Inductive Inference of Term Rewriting Systems from Positive Data 
M. R. K. Krishna Rao  
Learning Tree Languages from Positive Examples and Membership Queries 
Jérome Besombes and JeanYves Marion  
Boosting Based on Divide and Merge 
Eiji Takimoto, Syuhei Koya, and Akira Maruoka  
On the Data Consumption Benefits of Accepting Increased Uncertainty 
Eric Martin, Arun Sharma, Frank Stephan  
The Subsumption Lattice and Query Learning 
Marta Arias and Roni Khardon  
Estimation of the Data Region Using Extremevalue Distributions

Kazuho Watanabe and Sumio Watanabe 

New Revision Algorithms 
Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán  
Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data 
Daniil Ryabko  
Maximum Entropy Principle in NonProbabilistic Setting 
V.P.Maslov and V.V.V'yugin  
Learning Boolean Functions in AC^{0} on Attribute and Classification Noise 
Akinobu Miyata, Jun Tarui and Etsuji Tomita  
Learning Content Sequencing in an Educational Environment According Student Needs 
Ana Iglesias, Paloma Martínez, Ricardo Aler and Fernando Fernández  
Full Information Game with Gains and Losses 
Chamy AllenbergNeeman and Benny Neeman 