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NIPS
2004
14 years 11 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
BMCBI
2010
172views more  BMCBI 2010»
14 years 4 months ago
Nonparametric identification of regulatory interactions from spatial and temporal gene expression data
Background: The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but ...
Anil Aswani, Soile V. E. Keränen, James Brown...
KDD
2004
ACM
114views Data Mining» more  KDD 2004»
15 years 10 months ago
Mining reference tables for automatic text segmentation
Automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data ...
Eugene Agichtein, Venkatesh Ganti
CLEF
2009
Springer
14 years 11 months ago
MorphoNet: Exploring the Use of Community Structure for Unsupervised Morpheme Analysis
This paper investigates a novel approach to unsupervised morphology induction relying on community detection in networks. In a first step, morphological transformation rules are a...
Delphine Bernhard
SG
2007
Springer
15 years 3 months ago
Correlating Text and Images: Concept and Evaluation
This paper presents the concept and an evaluation of a novel approach to support students to understand complex spatial relations and to learn unknown terms of a domain-specific t...
Timo Götzelmann, Pere-Pau Vázquez, Knu...