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» Near Optimal Dimensionality Reductions That Preserve Volumes
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ICIC
2005
Springer
13 years 11 months ago
Neighborhood Preserving Projections (NPP): A Novel Linear Dimension Reduction Method
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dim...
Yanwei Pang, Lei Zhang, Zhengkai Liu, Nenghai Yu, ...
CVPR
2006
IEEE
14 years 7 months ago
Three-Dimensional Volume Reconstruction Based on Trajectory Fusion from Confocal Laser Scanning Microscope Images
In this paper, we address the problem of 3D volume reconstruction from depth adjacent subvolumes (i.e., sets of image frames) acquired using a confocal laser scanning microscope (...
Sang-Chul Lee, Peter Bajcsy
ML
2010
ACM
13 years 4 months ago
Semi-supervised local Fisher discriminant analysis for dimensionality reduction
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
Masashi Sugiyama, Tsuyoshi Idé, Shinichi Na...
NIPS
2003
13 years 7 months ago
Locality Preserving Projections
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...
Xiaofei He, Partha Niyogi
USS
2010
13 years 3 months ago
SEPIA: Privacy-Preserving Aggregation of Multi-Domain Network Events and Statistics
Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that ...
Martin Burkhart, Mario Strasser, Dilip Many, Xenof...