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» A statistical approach to rule learning
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IAT
2009
IEEE
16 years 1 months ago
An Intelligent Agent That Autonomously Learns How to Translate
—We describe the design of an autonomous agent that can teach itself how to translate from a foreign language, by first assembling its own training set, then using it to improve...
Marco Turchi, Tijl De Bie, Nello Cristianini
TNN
2008
85views more  TNN 2008»
15 years 6 months ago
Training Spiking Neuronal Networks With Applications in Engineering Tasks
In this paper, spiking neuronal models employing means, variances, and correlations for computation are introduced. We present two approaches in the design of spiking neuronal netw...
Phill Rowcliffe, Jianfeng Feng
IEAAIE
2001
Springer
15 years 11 months ago
Selecting a Relevant Set of Examples to Learn IE-Rules
The growing availability of online text has lead to an increase in the use of automatic knowledge acquisition approaches from textual data, as in Information Extraction (IE). Some ...
Jordi Turmo, Horacio Rodríguez
PR
2008
104views more  PR 2008»
15 years 6 months ago
Generative models for similarity-based classification
A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...
Luca Cazzanti, Maya R. Gupta, Anjali J. Koppal
ICML
2004
IEEE
16 years 7 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng