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» Learning to learn with the informative vector machine
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ICML
2003
IEEE
16 years 7 months ago
An Analysis of Rule Evaluation Metrics
In this paper we analyze the most popular evaluation metrics for separate-and-conquer rule learning algorithms. Our results show that all commonly used heuristics, including accur...
Johannes Fürnkranz, Peter A. Flach
195
Voted
IJCNN
2008
IEEE
16 years 1 months ago
Adaptive curiosity for emotions detection in speech
— Exploratory activities seem to be crucial for our cognitive development. According to psychologists, exploration is an intrinsically rewarding behaviour. The developmental robo...
Alexis Bondu, Vincent Lemaire
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
15 years 7 months ago
Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Greg Paperin
BMCBI
2004
140views more  BMCBI 2004»
15 years 6 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
ICANN
2010
Springer
15 years 4 months ago
Learning in a Unitary Coherent Hippocampus
Abstract. A previous paper [2] presented a model (UCPF-HC) of the hippocampus as a unitary coherent particle filter, which combines the classical hippocampal roles of associative m...
Charles W. Fox, Tony J. Prescott