Searching for "Geometric Data Analysis" – sorted by Relevance.
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Density-based cluster algorithms in lowdimensional and high-dimensional application
- illustrates the strengths and weaknesses of both algorithms on the basis of geometric data analysis
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Allgemeines Statistisches Archiv 88, 133--135
- . Modern geometrical data analysis begins in the mid-seventies with Tukey (1975), who, focussing
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Extensible infrastructure for a 3D face and vocal-tract model
- for articulatory gestures, and (3) validation through geometric data analysis. Additional data originates from
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partitioning and data set parameterization
- and eigenvalues) of a pairwise similarity matrix for geometric data analysis. These methods can roughly be divided
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Manifold Embeddings for Model-Based Reinforcement Learning of Neurostimulation Policies
- learning. Proceedings of ICML. Kirby, M. (2001). Geometric data analysis: An empirical approach
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Surface from scattered points - a brief survey of recent developments
- data analysis [33, 53] in pattern recognition [44], statistical learning [36], and neural networks [37
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Geodesic Delaunay triangulation and witness complex in the plane. Full version.http://geometry.stanford.edu/papers/ ggow-gdtwcp-08/ggow-gdtwcp-08-full.pdf
- and information discovery in sensor networks, etc. Recent advances in geometric data analysis and in sensor
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