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NN
2000
Springer
159views Neural Networks» more  NN 2000»
15 years 5 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 5 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 7 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 11 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 7 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...