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NN
2000
Springer
159views Neural Networks» more  NN 2000»
15 years 4 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
PAMI
2002
114views more  PAMI 2002»
15 years 4 months ago
Principal Manifolds and Probabilistic Subspaces for Visual Recognition
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
Baback Moghaddam
DAC
2006
ACM
16 years 5 months ago
Statistical timing analysis with correlated non-gaussian parameters using independent component analysis
We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...
Jaskirat Singh, Sachin S. Sapatnekar
DOCENG
2003
ACM
15 years 9 months ago
Accuracy improvement of automatic text classification based on feature transformation
In this paper, we describe a comparative study on techniques of feature transformation and classification to improve the accuracy of automatic text classification. The normalizati...
Guowei Zu, Wataru Ohyama, Tetsushi Wakabayashi, Fu...
NIPS
1994
15 years 5 months ago
Analysis of Unstandardized Contributions in Cross Connected Networks
Understanding knowledge representations in neural nets has been a difficult problem. Principal components analysis (PCA) of contributions (products of sending activations and conn...
Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Tak...