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12/21/2022
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression
We investigate the frequentist properties of the variational sparse Gaus...
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02/10/2022
Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case
With the development of new sensors and monitoring devices, more sources...
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02/02/2022
Optimal high-dimensional and nonparametric distributed testing under communication constraints
We derive minimax testing errors in a distributed framework where the da...
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09/22/2021
Contraction rates for sparse variational approximations in Gaussian process regression
We study the theoretical properties of a variational Bayes method in the...
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12/09/2020
Optimal distributed testing in high-dimensional Gaussian models
In this paper study the problem of signal detection in Gaussian noise in...
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03/28/2020
Distributed function estimation: adaptation using minimal communication
We investigate whether in a distributed setting, adaptive estimation of ...
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04/13/2018
Nonparametric Bayesian label prediction on a large graph using truncated Laplacian regularization
This article describes an implementation of a nonparametric Bayesian app...
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04/03/2018
Adaptive distributed methods under communication constraints
We study distributed estimation methods under communication constraints ...
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11/08/2017