Sciweavers

ALT
2006
Springer
13 years 8 months ago
Learning and Extending Sublanguages
A number of natural models for learning in the limit is introduced to deal with the situation when a learner is required to provide a grammar covering the input even if only a par...
Sanjay Jain, Efim B. Kinber
ALT
2006
Springer
13 years 8 months ago
Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring
In this paper the sequential prediction problem with expert advice is considered when the loss is unbounded under partial monitoring scenarios. We deal with a wide class of the par...
Chamy Allenberg, Peter Auer, László ...
ALT
2006
Springer
14 years 1 months ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
ALT
2006
Springer
14 years 1 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama
ALT
2006
Springer
14 years 1 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
ALT
2006
Springer
14 years 1 months ago
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
Hsuan-Tien Lin, Ling Li
ALT
2006
Springer
14 years 1 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri