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» Dimensionality reduction and generalization
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CVPR
2007
IEEE
14 years 12 months ago
Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
CIDM
2007
IEEE
14 years 4 months ago
Scalable Clustering for Large High-Dimensional Data Based on Data Summarization
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
ISVLSI
2003
IEEE
91views VLSI» more  ISVLSI 2003»
14 years 3 months ago
Three-Dimensional Integrated Circuits: Performance, Design Methodology, and CAD Tools
Three-dimensional integration technologies have been proposed in order to mitigate design challenges posed by deep-submicron interconnect. By providing multiple layers of active d...
Shamik Das, Anantha Chandrakasan, Rafael Reif
SCL
2008
95views more  SCL 2008»
13 years 9 months ago
Approximate reduction of dynamic systems
The reduction of dynamic systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically p...
Paulo Tabuada, Aaron D. Ames, A. Agung Julius, Geo...
ECCV
2006
Springer
14 years 11 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...