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» EM in High Dimensional Spaces
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SIAMSC
2008
198views more  SIAMSC 2008»
15 years 10 days 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
184
Voted
SIGMOD
2006
ACM
110views Database» more  SIGMOD 2006»
16 years 17 days 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...
ICDE
2000
IEEE
168views Database» more  ICDE 2000»
16 years 1 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
152
Voted
TIP
2008
177views more  TIP 2008»
15 years 9 days 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
116
Voted
KES
2006
Springer
15 years 11 days 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