Zobrazeno 1 - 10
of 134
pro vyhledávání: '"van Zanten, Harry"'
Combining test statistics from independent trials or experiments is a popular method of meta-analysis. However, there is very limited theoretical understanding of the power of the combined test, especially in high-dimensional models considering compo
Externí odkaz:
http://arxiv.org/abs/2310.19541
Autor:
Magra, Adel, van Zanten, Harry
We consider a Bayesian approach for the recovery of the thermal diffusivity for the heat equation when the initial temperature map of the system is unknown. This is a semiparametric inverse problem as the diffusivity is a one-dimensional parameter wh
Externí odkaz:
http://arxiv.org/abs/2310.02883
We investigate the frequentist guarantees of the variational sparse Gaussian process regression model. In the theoretical analysis, we focus on the variational approach with spectral features as inducing variables. We derive guarantees and limitation
Externí odkaz:
http://arxiv.org/abs/2212.11031
With the development of new sensors and monitoring devices, more sources of data become available to be used as inputs for machine learning models. These can on the one hand help to improve the accuracy of a model. On the other hand, combining these
Externí odkaz:
http://arxiv.org/abs/2202.05069
We derive minimax testing errors in a distributed framework where the data is split over multiple machines and their communication to a central machine is limited to $b$ bits. We investigate both the $d$- and infinite-dimensional signal detection pro
Externí odkaz:
http://arxiv.org/abs/2202.00968
We study the theoretical properties of a variational Bayes method in the Gaussian Process regression model. We consider the inducing variables method introduced by Titsias (2009a) and derive sufficient conditions for obtaining contraction rates for t
Externí odkaz:
http://arxiv.org/abs/2109.10755
In this paper we study the problem of signal detection in Gaussian noise in a distributed setting where the local machines in the star topology can communicate a single bit of information. We derive a lower bound on the Euclidian norm that the signal
Externí odkaz:
http://arxiv.org/abs/2012.04957
Autor:
Szabo, Botond, van Zanten, Harry
We investigate whether in a distributed setting, adaptive estimation of a smooth function at the optimal rate is possible under minimal communication. It turns out that the answer depends on the risk considered and on the number of servers over which
Externí odkaz:
http://arxiv.org/abs/2003.12838
Publikováno v:
In Journal of Computational Mathematics and Data Science December 2023 9
Autor:
Hartog, Jarno, van Zanten, Harry
This article describes an implementation of a nonparametric Bayesian approach to solving binary classification problems on graphs. We consider a hierarchical Bayesian approach with a prior that is constructed by truncating a series expansion of the s
Externí odkaz:
http://arxiv.org/abs/1804.07262