Futoshi Futami | DeepAI

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∙ 07/23/2023

Information-theoretic Analysis of Test Data Sensitivity in Uncertainty

Bayesian inference is often utilized for uncertainty quantification task...

0 Futoshi Futami, et al. ∙

∙ 06/02/2022

Excess risk analysis for epistemic uncertainty with application to variational inference

We analyze the epistemic uncertainty (EU) of supervised learning in Baye...

0 Futoshi Futami, et al. ∙

∙ 06/09/2021

Loss function based second-order Jensen inequality and its application to particle variational inference

Bayesian model averaging, obtained as the expectation of a likelihood fu...

0 Futoshi Futami, et al. ∙

∙ 03/10/2020

Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time

The Gaussian process bandit is a problem in which we want to find a maxi...

9 Hideaki Imamura, et al. ∙

∙ 05/21/2018

Frank-Wolfe Stein Sampling

In Bayesian inference, the posterior distributions are difficult to obta...

0 Futoshi Futami, et al. ∙

∙ 10/18/2017

Variational Inference based on Robust Divergences

Robustness to outliers is a central issue in real-world machine learning...

1 Futoshi Futami, et al. ∙

∙ 05/25/2017

Expectation Propagation for t-Exponential Family Using Q-Algebra

Exponential family distributions are highly useful in machine learning s...

0 Futoshi Futami, et al. ∙

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