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ACL
1998
13 years 10 months ago
Maximum Entropy Model Learning of the Translation Rules
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
Kengo Sato, Masakazu Nakanishi
ICONIP
1998
13 years 10 months ago
ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
Nikola K. Kasabov
IRMA
2000
13 years 10 months ago
Recognizing bounds of context change in on-line learning
The on-line algorithms in machine learning are intended to discover unknown function of the domain based on incremental observing of it instance by instance. These algorithms have...
Helen Kaikova, Vagan Y. Terziyan, Borys Omelayenko
AIPS
1994
13 years 10 months ago
Robot Motion Planning Integrating Planning Strategies and Learning Methods
Robot motion planning in a dynamic cluttered workspace requires the capability of dealing with obstacles and deadlock situations. The paper analyzes situations where the robot is ...
Luca Maria Gambardella, Cristina Versino
GBRPR
2007
Springer
14 years 1 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...