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Titlebook: Geometric Science of Information; First International Frank Nielsen,Frédéric Barbaresco Conference proceedings 2013 Springer-Verlag Berlin

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書(shū)目名稱Geometric Science of Information
副標(biāo)題First International
編輯Frank Nielsen,Frédéric Barbaresco
視頻videohttp://file.papertrans.cn/384/383609/383609.mp4
概述Fast track conference proceedings.Unique visibility.State of the art research
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Geometric Science of Information; First International  Frank Nielsen,Frédéric Barbaresco Conference proceedings 2013 Springer-Verlag Berlin
描述.This book constitutes the refereed proceedings of the First International Conference on Geometric Science of Information, GSI 2013, held in Paris, France, in August 2013. The nearly 100 papers presented were carefully reviewed and selected from numerous submissions and are organized into the following thematic sessions: Geometric Statistics on Manifolds and Lie Groups, Deformations in Shape Spaces, Differential Geometry in Signal Processing, Relational Metric, Discrete Metric Spaces, Computational Information Geometry, Hessian Information Geometry I and II, Computational Aspects of Information Geometry in Statistics, Optimization on Matrix Manifolds, Optimal Transport Theory, Probability on Manifolds, Divergence Geometry and Ancillarity, Entropic Geometry, Tensor-Valued Mathematical Morphology, Machine/Manifold/Topology Learning, Geometry of Audio Processing, Geometry of Inverse Problems, Algebraic/Infinite dimensional/Banach Information Manifolds, Information Geometry Manifolds, and Algorithms on Manifolds..
出版日期Conference proceedings 2013
關(guān)鍵詞affine differential geometry; complex projective space; ensemble methods; mathematical morphology; stoch
版次1
doihttps://doi.org/10.1007/978-3-642-40020-9
isbn_softcover978-3-642-40019-3
isbn_ebook978-3-642-40020-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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https://doi.org/10.1007/978-1-349-09265-9 image. However, Schild’s Ladder may be inefficient in case of time series of multiple time points, in which the computation of the geodesic diagonals is required several times. In this paper we propose a new algorithm, the Pole Ladder, in which one diagonal of the parallelogram is the baseline-to-r
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https://doi.org/10.1007/978-1-349-10473-4ow that we can decrease the number of model parameters (from the number of voxels down to hundreds) with only minimal decrease in model accuracy. The reduction in model parameters has the potential to improve the power of ensuing statistical analysis, which faces the challenging problem of high dime
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Parallel Transport with Pole Ladder: Application to Deformations of Time Series of Images image. However, Schild’s Ladder may be inefficient in case of time series of multiple time points, in which the computation of the geodesic diagonals is required several times. In this paper we propose a new algorithm, the Pole Ladder, in which one diagonal of the parallelogram is the baseline-to-r
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