Results 151 to 160 of about 7,842 (187)

Preconditioner Design via Bregman Divergences

SIAM Journal on Matrix Analysis and Applications
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Andreas A. Bock, Martin S. Andersen
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Similarity search on Bregman divergence

Proceedings of the VLDB Endowment, 2009
In this paper, we examine the problem of indexing over non-metric distance functions. In particular, we focus on a general class of distance functions, namely Bregman Divergence [6], to support nearest neighbor and range queries.
Zhang, Z., Ooi, B.C., Parthasarathy, S., Tung, A.K.H   +3 more
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Extending Metric Multidimensional Scaling with Bregman Divergences

Pattern Recognition, 2010
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Sun, Jigang, Crowe, Malcolm, Fyfe, Colin
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Information Geometry of U-Boost and Bregman Divergence

Neural Computation, 2004
We aim at an extension of AdaBoost to U-Boost, in the paradigm to build a stronger classification machine from a set of weak learning machines. A geometric understanding of the Bregman divergence defined by a generic convex function U leads to the U-Boost method in the framework of information geometry extended to the space of the finite measures over
Murata, N., Takenouchi, T., Kanamori, T., Eguchi, S.   +3 more
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Bregman Divergences from Comparative Convexity

2017
Comparative convexity is a generalization of ordinary convexity based on abstract means instead of arithmetic means. We define and study the Bregman divergences with respect to comparative convexity. As an example, we consider the convexity induced by quasi-arithmetic means, report explicit formulas, and show that those Bregman divergences are ...
Frank Nielsen, Richard Nock
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Bregman divergences in the -partitioning problem

Computational Statistics & Data Analysis, 2006
A method of fixed cardinality partition is examined. This methodology can be applied on many problems, such as the confidentiality protection, in which the protection of confidential information has to be ensured, while preserving the information content of the data.
G. Kokolakis, Ph. Nanopoulos, D. Fouskakis   +2 more
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Segmenting Coloured Images Using Bregman Divergence

2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), 2018
Image segmentation is required for many applications of object recognition. It can be achieved through clustering in a partition based approach. K-means is a fast and efficient method for segmenting image into predefined number of regions. We propose how to improve its performance using Bregman divergences to measure similarity between two pixels ...
Anjuman Ara Gauri, Iti Sharma
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Extending Sammon mapping with Bregman divergences

Information Sciences, 2012
The Sammon mapping has been one of the most successful nonlinear metric multidimensional scaling methods since its advent in 1969, but effort has been focused on algorithm improvement rather than on the form of the stress function. This paper further investigates using left Bregman divergences to extend the Sammon mapping and by analogy develops right ...
Jigang Sun, Colin Fyfe, Malcolm Crowe
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Bregman divergence as relative operator entropy

Acta Mathematica Hungarica, 2007
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Bregman Divergences and Multi-dimensional Scaling

2009
We discuss Bregman divergences and the very close relationship between a class of these divergences and the regular family of exponential distributions before applying them to various topology preserving dimension reducing algorithms. We apply these to multidimensional scaling (MDS) and show the effect of different Bregman divergences. In particular we
Pei Ling Lai, Colin Fyfe
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