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» Training Methods for Adaptive Boosting of Neural Networks
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ICIAP
2003
ACM
15 years 2 months ago
PCA vs low resolution images in face verification
Principal Components Analysis (PCA) has been one of the most applied methods for face verification using only 2D information, in fact, PCA is practically the method of choice for ...
Cristina Conde, Antonio Ruiz, Enrique Cabello
ICCV
2007
IEEE
15 years 11 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
73
Voted
NIPS
2003
14 years 11 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish
NN
2008
Springer
101views Neural Networks» more  NN 2008»
14 years 9 months ago
On multidimensional scaling and the embedding of self-organising maps
The self-organising map (SOM) and its variant, visualisation induced SOM (ViSOM), have been known to yield similar results to multidimensional scaling (MDS). However, the exact co...
Hujun Yin
NN
2010
Springer
183views Neural Networks» more  NN 2010»
14 years 8 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui