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SIAMSC
2008
198views more  SIAMSC 2008»
13 years 5 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
TSMC
2010
13 years 14 days ago
Fractional Particle Swarm Optimization in Multidimensional Search Space
In this paper, we propose two novel techniques, which successfully address several major problems in the field of particle swarm optimization (PSO) and promise a significant breakt...
Serkan Kiranyaz, Turker Ince, E. Alper Yildirim, M...
KES
2006
Springer
13 years 5 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
PODS
1997
ACM
182views Database» more  PODS 1997»
13 years 10 months ago
A Cost Model For Nearest Neighbor Search in High-Dimensional Data Space
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data space. We first analyze different nearest neighbor algorithms, present a generaliza...
Stefan Berchtold, Christian Böhm, Daniel A. K...
TASLP
2008
176views more  TASLP 2008»
13 years 5 months ago
Analysis of Minimum Distances in High-Dimensional Musical Spaces
Abstract--We propose an automatic method for measuring content-based music similarity, enhancing the current generation of music search engines and recommender systems. Many previo...
Michael Casey, Christophe Rhodes, Malcolm Slaney