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IJCAI
1997
14 years 11 months ago
Is Nonparametric Learning Practical in Very High Dimensional Spaces?
Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
Gregory Z. Grudic, Peter D. Lawrence
66
Voted
ICCBR
2007
Springer
15 years 3 months ago
Case-Based Reasoning Adaptation for High Dimensional Solution Space
Case-Based Reasoning (CBR) is a methodology that reuses the solutions of previous similar problems to solve new problems. Adaptation is the most difficult stage in the CBR cycle, e...
Ying Zhang, Panos Louvieris, Maria Petrou
92
Voted
ECML
2006
Springer
15 years 1 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
DMIN
2008
152views Data Mining» more  DMIN 2008»
14 years 11 months ago
PCS: An Efficient Clustering Method for High-Dimensional Data
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Wei Li 0011, Cindy Chen, Jie Wang
CEC
2007
IEEE
15 years 1 months ago
Virtual reality high dimensional objective spaces for multi-objective optimization: An improved representation
This paper presents an approach for constructing improved visual representations of high dimensional objective spaces using virtual reality. These spaces arise from the solution of...
Julio J. Valdés, Alan J. Barton, Robert Orc...