In this treat- ment, a direct approach is to formulate a standard. Page 2. Gaussian Process Multiple Instance Learning. (instance-level) classification problem ...
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Bayesian linear regression is also directly related to a nonparametric approach known as Gaussian process prediction (e.g., [10]), in which predictions about ...
PDF | On Apr 1, 2018, Fredrik Wahlberg published Gaussian Process Classification as Metric Learning for Forensic Writer Identification | Find, read and cite ...
Furthermore, this method uses the concept of a standardised GP process and allows for learning Mahalanobis distance metrics (Weinberger and. Saul, 2009; Xing et ...
Aug 15, 2018 · The metric learning inference was based on multiclass Gaussian process classification. Using the popular datasets IAM and CVL combined, the ...
Mar 19, 2018 · Abstract:This work incorporates the multi-modality of the data distribution into a Gaussian Process regression model.
Gaussian Processes for Machine Learning presents one of the most important. Bayesian machine learning approaches ... metric positive semidefinite, its eigenvalues ...
We present a novel method for learning with Gaussian process regres- sion in a hierarchical Bayesian framework. In a first step, kernel matri- ces on a ...
Furthermore, this method uses the concept of a standardised GP process and allows for learning Mahalanobis distance metrics (Weinberger and. Saul, 2009; Xing et ...
... Gaussian Processes for Machine Learning, C. E. Rasmussen ... High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning.