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» EM in High Dimensional Spaces
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107
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SIAMSC
2008
198views more  SIAMSC 2008»
14 years 10 months ago
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
T. Bui-Thanh, Karen Willcox, Omar Ghattas
167
Voted
SIGMOD
2006
ACM
110views Database» more  SIGMOD 2006»
15 years 10 months ago
Finding k-dominant skylines in high dimensional space
Given a d-dimensional data set, a point p dominates another point q if it is better than or equal to q in all dimensions and better than q in at least one dimension. A point is a ...
Chee Yong Chan, H. V. Jagadish, Kian-Lee Tan, Anth...
191
Voted
ICDE
2000
IEEE
168views Database» more  ICDE 2000»
15 years 11 months ago
PAC Nearest Neighbor Queries: Approximate and Controlled Search in High-Dimensional and Metric Spaces
In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
Paolo Ciaccia, Marco Patella
117
Voted
TIP
2008
177views more  TIP 2008»
14 years 10 months ago
Visual Tracking in High-Dimensional State Space by Appearance-Guided Particle Filtering
Abstract--In this paper, we propose a new approach, appearance-guided particle filtering (AGPF), for high degree-of-freedom visual tracking from an image sequence. This method adop...
Wen-Yan Chang, Chu-Song Chen, Yong-Dian Jian
KES
2006
Springer
14 years 10 months ago
Genetic-Fuzzy Modeling on High Dimensional Spaces
In this paper, in order to reduce the explosive increase of the search space as the input dimension grows, we present a new representation method for the structure of fuzzy rules, ...
Joon-Min Gil, SeongHoon Lee