Results 1 to 10 of about 375,379 (320)
Intrinsic Metric Learning With Subspace Representation [PDF]
IEEE Access, 2019 The accuracy of classification and retrieval significantly depends on the metric used to compute the similarity between samples. For preserving the geometric structure, the symmetric positive definite (SPD) manifold is introduced into the metric learning
Lipeng Cai +4 more
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Approximate reasoning for real-time probabilistic processes [PDF]
Logical Methods in Computer Science, 2006 We develop a pseudo-metric analogue of bisimulation for generalized semi-Markov processes. The kernel of this pseudo-metric corresponds to bisimulation; thus we have extended bisimulation for continuous-time probabilistic processes to a much broader ...
Vineet Gupta +2 more
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Intrinsic metrics in polygonal domains [PDF]
Mathematische Nachrichten, 2023 AbstractWe study inequalities between the hyperbolic metric and intrinsic metrics in convex polygonal domains in the complex plane. A special attention is paid to the triangular ratio metric in rectangles. A local study leads to investigation of the relationship between the conformal radius at an arbitrary point of a planar domain and the distance of ...
D. Dautova +3 more
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Surface Simplification using Intrinsic Error Metrics [PDF]
ACM Transactions on Graphics, 2023 This paper describes a method for fast simplification of surface meshes. Whereas past methods focus on visual appearance, our goal is to solve equations on the surface. Hence, rather than approximate the extrinsic geometry, we construct a coarse intrinsic triangulation of the input domain. In the spirit of the
Hsueh‐Ti Derek Liu +5 more
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On the holomorphic curvature of some intrinsic metrics [PDF]
Proceedings of the American Mathematical Society, 1977 If G is a hyperbolic manifold in the sense of Kobayashi and the differential Kobayashi metric K G {K_G} is of class C 2 {C^2} , then the holomorphic curvature of K G {K_G} is greater than or ...
Benjamin Wong
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An intrinsic metric for power spectral density functions [PDF]
IEEE Signal Processing Letters, 2006 We present an intrinsic metric that quantifies distances between power spectral density functions. The metric was derived by the author in a recent arXiv-report (math.OC/0607026) as the geodesic distance between spectral density functions with respect to
Georgiou, Tryphon T.
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Universal coding, intrinsic volumes, and metric complexity
Journal of the European Mathematical SocietyWe study sequential probability assignment in the Gaussian setting, where the goal is to predict, or equivalently compress, a sequence of real-valued observations almost as well as the best Gaussian distribution with mean constrained to a given subset of \mathbb{R}^{n} .
Jaouad Mourtada
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Local Equivalence and Intrinsic Metrics between Reeb Graphs
, 2017 As graphical summaries for topological spaces and maps, Reeb graphs are common objects in the computer graphics or topological data analysis literature. Defining good metrics between these objects has become an important question for applications, where it matters to quantify the extent by which two given Reeb graphs differ.
Mathieu Carrière, Steve Oudot
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Optimization of clustering parameters for single-cell RNA analysis using intrinsic goodness metrics. [PDF]
Front BioinformSciaraffa N +3 more
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Introducing a New Intrinsic Metric [PDF]
Results in Mathematics, 2022 AbstractA new intrinsic metric called the t-metric is introduced. Several sharp inequalities between this metric and the most common hyperbolic type metrics are proven for various domains $$G\subsetneq \mathbb {R}^n$$ G ⊊ R
Oona Rainio, Matti Vuorinen
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