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IJCNN
2006
IEEE
14 years 2 months ago
Preparing More Effective Liquid State Machines Using Hebbian Learning
—In Liquid State Machines, separation is a critical attribute of the liquid—which is traditionally not trained. The effects of using Hebbian learning in the liquid to improve s...
David Norton, Dan Ventura
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
ECRIME
2007
13 years 12 months ago
A comparison of machine learning techniques for phishing detection
There are many applications available for phishing detection. However, unlike predicting spam, there are only few studies that compare machine learning techniques in predicting ph...
Saeed Abu-Nimeh, Dario Nappa, Xinlei Wang, Suku Na...
TROB
2008
207views more  TROB 2008»
13 years 7 months ago
Learning Object Affordances: From Sensory-Motor Coordination to Imitation
Affordances encode relationships between actions, objects and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the p...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
EMNLP
2006
13 years 9 months ago
Competitive generative models with structure learning for NLP classification tasks
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
Kristina Toutanova