Results 31 to 40 of about 500 (159)
Learning to Approximate a Bregman Divergence
CoRR, 2019 19 pages, 4 ...
Ali Siahkamari +4 more
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Update of Prior Probabilities by Minimal Divergence
Entropy, 2021 The present paper investigates the update of an empirical probability distribution with the results of a new set of observations. The update reproduces the new observations and interpolates using prior information.
Jan Naudts
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Hessian geometric structure of chemical thermodynamic systems with stoichiometric constraints
Physical Review Research, 2022 We establish a Hessian geometric structure in chemical thermodynamics, which describes chemical reaction networks (CRNs) with equilibrium states. In our setup, the ideal gas assumption and mass action kinetics are not required.
Yuki Sughiyama +3 more
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Parametric Bayesian Estimation of Differential Entropy and Relative Entropy
Entropy, 2010 Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform ...
Maya Gupta, Santosh Srivastava
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Neural Bregman Divergences for Distance Learning
CoRR, 2022 Many metric learning tasks, such as triplet learning, nearest neighbor retrieval, and visualization, are treated primarily as embedding tasks where the ultimate metric is some variant of the Euclidean distance (e.g., cosine or Mahalanobis), and the algorithm must learn to embed points into the pre-chosen space.
Fred Lu, Edward Raff, Francis Ferraro
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Bregman superquantiles. Estimation methods and applications
Dependence Modeling, 2016 In thiswork,we extend some parameters built on a probability distribution introduced before to the casewhere the proximity between real numbers is measured by using a Bregman divergence.
Labopin-Richard T. +3 more
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Matrix Nearness Problems with Bregman Divergences [PDF]
SIAM Journal on Matrix Analysis and Applications, 2008 This paper discusses a new class of matrix nearness problems that measure approximation error using a directed distance measure called a Bregman divergence. Bregman divergences offer an important generalization of the squared Frobenius norm and relative entropy, and they all share fundamental geometric properties.
Inderjit S. Dhillon, Joel A. Tropp
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Divergence Family Contribution to Data Evaluation in Blockchain Via Alpha-EM and Log-EM Algorithms
IEEE Access, 2021 This study interrelates three adjacent topics in data evaluation. The first is the establishment of a relationship between Bregman divergence and probabilistic alpha-divergence.
Yasuo Matsuyama
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Preconditioner Design via the Bregman Divergence
CoRR, 2023 We study a preconditioner for a Hermitian positive definite linear system, which is obtained as the solution of a matrix nearness problem based on the Bregman log determinant divergence. The preconditioner is of the form of a Hermitian positive definite matrix plus a low-rank matrix.
Andreas A. Bock, Martin S. Andersen 0001
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CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 As one spatio-temporal data mining task, clustering helps the exploration of patterns in the data by grouping similar elements together. However, previous studies on spatial or temporal clustering are incapable of analysing complex patterns in spatio ...
X. Wu +3 more
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