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04/19/2023
Information Geometrically Generalized Covariate Shift Adaptation
Many machine learning methods assume that the training and test data fol...
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11/18/2022
Active Learning by Query by Committee with Robust Divergences
Active learning is a widely used methodology for various problems with h...
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09/10/2022
Unsupervised Domain Adaptation for Extra Features in the Target Domain Using Optimal Transport
Domain adaptation aims to transfer knowledge of labeled instances obtain...
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09/09/2022
Gaussian Process Koopman Mode Decomposition
In this paper, we propose a nonlinear probabilistic generative model of ...
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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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06/23/2022
Gradual Domain Adaptation via Normalizing Flows
Conventional domain adaptation methods do not work well when a large gap...
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06/22/2022
Information Geometry of Dropout Training
Dropout is one of the most popular regularization techniques in neural n...
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02/15/2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
Local differential privacy (LDP) is an information-theoretic privacy def...
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02/09/2022
Cost-effective Framework for Gradual Domain Adaptation with Multifidelity
In domain adaptation, when there is a large distance between the source ...
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06/01/2021
Fast symplectic integrator for Nesterov-type acceleration method
In this paper, explicit stable integrators based on symplectic and conta...
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04/05/2021
Stopping Criterion for Active Learning Based on Error Stability
Active learning is a framework for supervised learning to improve the pr...
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03/31/2021
α-Geodesical Skew Divergence
The asymmetric skew divergence smooths one of the distributions by mixin...
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12/08/2020
Active Learning: Problem Settings and Recent Developments
In supervised learning, acquiring labeled training data for a predictive...
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08/07/2020
Modal Principal Component Analysis
Principal component analysis (PCA) is a widely used method for data proc...
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05/15/2020
Stopping criterion for active learning based on deterministic generalization bounds
Active learning is a framework in which the learning machine can select ...
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01/07/2020
Fast and robust multiplane single molecule localization microscopy using deep neural network
Single molecule localization microscopy is widely used in biological res...
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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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05/07/2019
Bayesian Optimization for Multi-objective Optimization and Multi-point Search
Bayesian optimization is an effective method to efficiently optimize unk...
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05/31/2018
Classification of volcanic ash particles using a convolutional neural network and probability
Analyses of volcanic ash are typically performed either by qualitatively...
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12/02/2015
Double Sparse Multi-Frame Image Super Resolution
A large number of image super resolution algorithms based on the sparse ...
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02/14/2012