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09/03/2022
Geometry of EM and related iterative algorithms
The Expectation–Maximization (EM) algorithm is a simple meta-algorithm t...
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02/17/2022
Full-Span Log-Linear Model and Fast Learning Algorithm
The full-span log-linear(FSLL) model introduced in this paper is conside...
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12/03/2021
Learning Curves for Sequential Training of Neural Networks: Self-Knowledge Transfer and Forgetting
Sequential training from task to task is becoming one of the major objec...
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07/15/2021
Principal component analysis for Gaussian process posteriors
This paper proposes an extension of principal component analysis for Gau...
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07/02/2021
Reconsidering Dependency Networks from an Information Geometry Perspective
Dependency networks (Heckerman et al., 2000) are potential probabilistic...
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10/14/2019
Pathological spectra of the Fisher information metric and its variants in deep neural networks
The Fisher information matrix (FIM) plays an essential role in statistic...
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09/27/2019
On a convergence property of a geometrical algorithm for statistical manifolds
In this paper, we examine a geometrical projection algorithm for statist...
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06/07/2019
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
Normalization methods play an important role in enhancing the performanc...
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06/04/2018
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
This study analyzes the Fisher information matrix (FIM) by applying mean...
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09/13/2006
A kernel method for canonical correlation analysis
Canonical correlation analysis is a technique to extract common features...
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11/07/2002