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Projections with Logarithmic Divergences

Part of the Lecture Notes in Computer Science book series (LNIP,volume 12829)


In information geometry, generalized exponential families and statistical manifolds with curvature are under active investigation in recent years. In this paper we consider the statistical manifold induced by a logarithmic \(L^{(\alpha )}\)-divergence which generalizes the Bregman divergence. It is known that such a manifold is dually projectively flat with constant negative sectional curvature, and is closely related to the \(\mathcal {F}^{(\alpha )}\)-family, a generalized exponential family introduced by the second author [16]. Our main result constructs a dual foliation of the statistical manifold, i.e., an orthogonal decomposition consisting of primal and dual autoparallel submanifolds. This decomposition, which can be naturally interpreted in terms of primal and dual projections with respect to the logarithmic divergence, extends the dual foliation of a dually flat manifold studied by Amari [1]. As an application, we formulate a new \(L^{(\alpha )}\)-PCA problem which generalizes the exponential family PCA [5].


  • Logarithmic divergence
  • Generalized exponential family
  • Dual foliation
  • Projection
  • Principal component analysis

This research is supported by NSERC Discovery Grant RGPIN-2019-04419 and a Connaught New Researcher Award.

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Correspondence to Ting-Kam Leonard Wong .

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Tao, Z., Wong, TK.L. (2021). Projections with Logarithmic Divergences. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2021. Lecture Notes in Computer Science(), vol 12829. Springer, Cham.

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