Results 31 to 40 of about 1,600,993 (289)
Divergence Functions in Information Geometry [PDF]
, 2019 10 ...
Nihat Ay, Domenico Felice
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The Information Geometry of Mirror Descent [PDF]
IEEE Transactions on Information Theory, 2015 Information geometry applies concepts in differential geometry to probability and statistics and is especially useful for parameter estimation in exponential families where parameters are known to lie on a Riemannian manifold. Connections between the geometric properties of the induced manifold and statistical properties of the estimation problem are ...
Garvesh Raskutti, Sayan Mukherjee
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Information Geometry for Covariance Estimation in Heterogeneous Clutter with Total Bregman Divergence [PDF]
Entropy, 2018 This paper presents a covariance matrix estimation method based on information geometry in a heterogeneous clutter. In particular, the problem of covariance estimation is reformulated as the computation of geometric median for covariance matrices ...
Xiaoqiang Hua +3 more
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Kählerian Information Geometry for Signal Processing
Entropy, 2015 We prove the correspondence between the information geometry of a signal filter and a Kähler manifold. The information geometry of a minimum-phase linear system with a finite complex cepstrum norm is a Kähler manifold.
Jaehyung Choi, Andrew P. Mullhaupt
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Information Geometry of κ-Exponential Families: Dually-Flat, Hessian and Legendre Structures [PDF]
Entropy, 2018 In this paper, we present a review of recent developments on the κ -deformed statistical mechanics in the framework of the information geometry.
Antonio M. Scarfone +2 more
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Eye movements and information geometry
Journal of the Optical Society of America A, 2016 The human visual system uses eye movements to gather visual information. They act as visual scanning processes and can roughly be divided into two different types: small movements around fixation points and larger movements between fixation points. The processes are often modeled as random walks, and recent models based on heavy tail distributions ...
Reiner Lenz
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Information Geometry of Randomized Quantum State Tomography [PDF]
Entropy, 2018 Suppose that a d-dimensional Hilbert space H ≃ C d admits a full set of mutually unbiased bases | 1 ( a ) 〉 , ⋯ , | d ( a ) 〉 , where a = 1 , ⋯ , d + 1 .
Akio Fujiwara, Koichi Yamagata
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Information Geometry of Nonlinear Stochastic Systems [PDF]
Entropy, 2018 We elucidate the effect of different deterministic nonlinear forces on geometric structure of stochastic processes by investigating the transient relaxation of initial PDFs of a stochastic variable x under forces proportional to -xn (n=3,5,7) and ...
Rainer Hollerbach +2 more
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From Information Geometry to Newtonian Dynamics [PDF]
, 2007 Newtonian dynamics is derived from prior information codified into an appropriate statistical model. The basic assumption is that there is an irreducible uncertainty in the location of particles so that the state of a particle is defined by a probability
Ariel Caticha +6 more
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The Information Geometry of Space and Time [PDF]
, 2005 Is the geometry of space a macroscopic manifestation of an underlying microscopic statistical structure? Is geometrodynamics - the theory of gravity - derivable from general principles of inductive inference? Tentative answers are suggested by a model of
Ariel Caticha
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