The 14th International Conference


Criterion of Calibration for Transductive Confidence Machine with
Limited Feedback

Ilia Nouretdinov, Vladimir Vovk
 
On the Complexity of Training a Single Perceptron with Programmable
Synaptic Delays

Jiri Sima  
Transductive Confidence Machine is Universal 
Ilia Nouretdinov, Vladimir V'yugin, Alex Gammerman  
Kernel Trick Embedded Gaussian Mixture Model 
Jianguo Lee, Jingdong Wang, Changshui Zhang  
A Stochastic Gradient Descent Algorithm for Structural Risk
Minimisation 
Joel Ratsaby  
On the Learnability of Erasing Pattern Languages in the Query Model

Steffen Lange, Sandra Zilles  
Intrinsic Complexity of Uniform Learning

Sandra Zilles  
On the Existence and Convergence of Computable Universal Priors 
Marcus Hutter  
Changing the Inference Type  Keeping the Hypothesis Space

Frank Balbach 

WellCalibrated Predictions from OnLine Compression Models

Vladimir Vovk  
Efficiently Learning the Metric with SideInformation 
Tijl De Bie, Michinari Momma, Nello Cristianini  
Learning a Subclass of Regular Patterns in Polynomial Time  John Case, Sanjay Jain, Rüdiger Reischuk, Frank Stephan, Thomas
Zeugmann


Identification with Probability One of Stochastic Deterministic Linear Languages 
Colin de la Higuera, Jose Oncina  
Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries  Satoshi Matsumoto, Yusuke Suzuki, Takayoshi Shoudai, Tetsuhiro
Miyahara, Tomoyuki Uchida 

Learning of Erasing Primitive Formal Systems from Positive Examples 
Jin Uemura and Masako Sato  
Learning Continuous Latent Variable Models with Bregman Divergences  Shaojun Wang and Dale Schuurmans 

Robust Inference of Relevant Attributes 
Jan Arpe Rüdiger Reischuk  
Efficient Learning of Ordered and
Unordered Tree Patterns with Contractible Variables 
Yusuke Suzuki, Takayoshi Shoudai, Satoshi Matsumoto, Tomoyuki Uchida, Tetsuhiro Miyahara  
On Ordinal VCDimension and Some Notions of Complexity 
Eric Martin, Frank Stephan, Arun Sharma 