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» Lossy Reduction for Very High Dimensional Data
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KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 6 days ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
DAC
2007
ACM
16 years 24 days ago
Fast Second-Order Statistical Static Timing Analysis Using Parameter Dimension Reduction
The ability to account for the growing impacts of multiple process variations in modern technologies is becoming an integral part of nanometer VLSI design. Under the context of ti...
Zhuo Feng, Peng Li, Yaping Zhan
NPL
1998
135views more  NPL 1998»
14 years 11 months ago
Local Adaptive Subspace Regression
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
Sethu Vijayakumar, Stefan Schaal
TIT
2008
73views more  TIT 2008»
14 years 11 months ago
L-CAMP: Extremely Local High-Performance Wavelet Representations in High Spatial Dimension
A new wavelet-based methodology for representing data on regular grids is introduced and studied. The main attraction of this new L-CAMP methodology is in the way it scales with th...
Youngmi Hur, Amos Ron
IEEEMM
2007
146views more  IEEEMM 2007»
14 years 11 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...