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» A Distance-Based Packing Method for High Dimensional Data
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IVC
2007
164views more  IVC 2007»
13 years 8 months ago
Locality preserving CCA with applications to data visualization and pose estimation
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
Tingkai Sun, Songcan Chen
ISSRE
2005
IEEE
14 years 2 months ago
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
The software development process imposes major impacts on the quality of software at every development stage; therefore, a common goal of each software development phase concerns ...
Fei Xing, Ping Guo, Michael R. Lyu
SDM
2007
SIAM
118views Data Mining» more  SDM 2007»
13 years 10 months ago
On Privacy-Preservation of Text and Sparse Binary Data with Sketches
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
Charu C. Aggarwal, Philip S. Yu
EDBT
2008
ACM
132views Database» more  EDBT 2008»
14 years 9 months ago
Indexing high-dimensional data in dual distance spaces: a symmetrical encoding approach
Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-bas...
Yi Zhuang, Yueting Zhuang, Qing Li, Lei Chen 0002,...
ICPR
2006
IEEE
14 years 10 months ago
3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis
In this paper, we apply a multiple regression method based on Canonical Correlation Analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the corre...
Michael Reiter, Rene Donner, Georg Langs, Horst Bi...