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» On the Performance of Clustering in Hilbert Spaces
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ICDE
2008
IEEE
158views Database» more  ICDE 2008»
14 years 9 months ago
CARE: Finding Local Linear Correlations in High Dimensional Data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Xiang Zhang, Feng Pan, Wei Wang
CIARP
2006
Springer
13 years 9 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...
TKDE
2010
137views more  TKDE 2010»
13 years 5 months ago
A Survey on Transfer Learning
—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
Sinno Jialin Pan, Qiang Yang
ASPLOS
1996
ACM
13 years 11 months ago
Shasta: A Low Overhead, Software-Only Approach for Supporting Fine-Grain Shared Memory
This paper describes Shasta, a system that supports a shared address space in software on clusters of computers with physically distributed memory. A unique aspect of Shasta compa...
Daniel J. Scales, Kourosh Gharachorloo, Chandramoh...
MMDB
2003
ACM
94views Multimedia» more  MMDB 2003»
14 years 24 days ago
Improving image retrieval effectiveness via multiple queries
Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...
Xiangyu Jin, James C. French