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» That Which Does Not Stabilize, Will Only Make Us Stronger
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IJON
2010
178views more  IJON 2010»
14 years 8 months ago
An empirical study of two typical locality preserving linear discriminant analysis methods
: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Lishan Qiao, Limei Zhang, Songcan Chen
88
Voted
RE
1997
Springer
15 years 1 months ago
Requirements Models in Context
The field of requirements engineering emerges out of tradition of research and engineering practice that stresses rtance of generalizations and abstractions. abstraction is essent...
Colin Potts
EATCS
1998
250views more  EATCS 1998»
14 years 9 months ago
Human Visual Perception and Kolmogorov Complexity: Revisited
Experiments have shown [2] that we can only memorize images up to a certain complexity level, after which, instead of memorizing the image itself, we, sort of, memorize a probabil...
Vladik Kreinovich, Luc Longpré
ICML
2007
IEEE
15 years 10 months ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu
89
Voted
SASN
2006
ACM
15 years 3 months ago
RANBAR: RANSAC-based resilient aggregation in sensor networks
We present a novel outlier elimination technique designed for sensor networks. This technique is called RANBAR and it is based on the RANSAC (RANdom SAmple Consensus) paradigm, wh...
Levente Buttyán, Péter Schaffer, Ist...