292 search results - page 7 / 59 » Grammatical inference as a principal component analysis prob... |
FPGA
2006
ACM
13 years 11 months ago
2006
ACM
In this paper, we develop an architecture for principal component analysis (PCA) to be used as an outlier detection method for high-speed network intrusion detection systems (NIDS...
KDD
2006
ACM
14 years 7 months ago
2006
ACM
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
JACM
2011
12 years 10 months ago
2011
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
JMLR
2010
13 years 2 months ago
2010
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...