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Publication
170views
11 years 5 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
IJAIT
2007
108views more  IJAIT 2007»
11 years 6 months ago
Document Retrieval by Projection Based Frequency Distribution
In document retrieval task, random projection (RP) is a useful technique of dimension reduction. It can be obtained very quickly yet the recalculation is not necessary to any chang...
Isamu Shioya, Hirohito Oh'uchi, Takao Miura
ICASSP
2010
IEEE
11 years 6 months ago
Evaluation of random-projection-based feature combination on speech recognition
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...
UAI
2000
11 years 7 months ago
Experiments with Random Projection
Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gaussians. Here we summarize these results and ...
Sanjoy Dasgupta
CIKM
2008
Springer
11 years 8 months ago
On low dimensional random projections and similarity search
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
Yu-En Lu, Pietro Liò, Steven Hand
SLSFS
2005
Springer
12 years 21 hour ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum
AI
2005
Springer
12 years 3 days ago
Comparing Dimension Reduction Techniques for Document Clustering
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
BIOWIRE
2007
Springer
12 years 22 days ago
Beta Random Projection
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. In particular, r...
Yu-En Lu, Pietro Liò, Steven Hand
KDD
2001
ACM
187views Data Mining» more  KDD 2001»
12 years 7 months ago
Random projection in dimensionality reduction: applications to image and text data
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
Ella Bingham, Heikki Mannila
DCC
2009
IEEE
12 years 7 months ago
Compressive-Projection Principal Component Analysis and the First Eigenvector
An analysis is presented that extends existing Rayleigh-Ritz theory to the special case of highly eccentric distributions. Specifically, a bound on the angle between the first Rit...
James E. Fowler
books