Sciweavers

114
Voted
ALT
2005
Springer
15 years 10 months ago
Learnability of Probabilistic Automata via Oracles
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
82
Voted
ALT
2005
Springer
15 years 10 months ago
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
Arthur Gretton, Olivier Bousquet, Alex J. Smola, B...
116
Voted
ALT
2005
Springer
15 years 10 months ago
Teaching Learners with Restricted Mind Changes
Within learning theory teaching has been studied in various ways. In a common variant the teacher has to teach all learners that are restricted to output only consistent hypotheses...
Frank J. Balbach, Thomas Zeugmann
97
Voted
ALT
2005
Springer
15 years 10 months ago
Monotone Conditional Complexity Bounds on Future Prediction Errors
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true ...
Alexey V. Chernov, Marcus Hutter
94
Voted
ALT
2005
Springer
15 years 10 months ago
Non U-Shaped Vacillatory and Team Learning
U-shaped learning behaviour in cognitive development involves learning, unlearning and relearning. It occurs, for example, in learning irregular verbs. The prior cognitive science...
Lorenzo Carlucci, John Case, Sanjay Jain, Frank St...
105
Voted
ALT
2006
Springer
15 years 10 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
127
Voted
ALT
2006
Springer
15 years 10 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