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COLT
1994
Springer
15 years 8 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
BC
2006
149views more  BC 2006»
15 years 4 months ago
Learning invariant object recognition in the visual system with continuous transformations
Abstract The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temp...
Simon M. Stringer, G. Perry, Edmund T. Rolls, J. H...
133
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ASUNAM
2010
IEEE
15 years 5 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen
ML
2006
ACM
15 years 4 months ago
Relational IBL in classical music
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
Asmir Tobudic, Gerhard Widmer
FLAIRS
2009
15 years 1 months ago
Mapping Grounded Object Properties across Perceptually Heterogeneous Embodiments
As robots become more common, it becomes increasingly useful for them to communicate and effectively share knowledge that they have learned through their individual experiences. L...
Zsolt Kira