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» Data Aggregation Sets in Adaptive Data Model
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ICASSP
2010
IEEE
15 years 6 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
IDEAL
2005
Springer
16 years 3 days ago
Cluster Analysis of High-Dimensional Data: A Case Study
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
Richard Bean, Geoffrey J. McLachlan
ECMDAFA
2006
Springer
226views Hardware» more  ECMDAFA 2006»
15 years 8 months ago
Definition and Generation of Data Exchange Formats in AUTOSAR
In this paper we present a methodology supporting the definition of data models on basis of a limited set of well-known UML features, thereby allowing these models to be created an...
Mike Pagel, Mark Brörkens
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 9 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
ADBIS
2007
Springer
256views Database» more  ADBIS 2007»
15 years 10 months ago
Adaptive k-Nearest-Neighbor Classification Using a Dynamic Number of Nearest Neighbors
Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high ...
Stefanos Ougiaroglou, Alexandros Nanopoulos, Apost...