A hierarchical Product of Expert model, which consist of multiple layers of small, independent and local GP experts is proposed, which scales well for large ...

Feb 20, 2019 · Sensing devices should be as small and as energy efficient as possible to minimize costs. 2. Sensing devices should be low-priced to ...

Furthermore, Gaussian Processes are a global and centralized model, which requires all measurements to be available at a central computation node. Product of ...

This paper develops a novel approach to queuing analysis tailor-made for multiscale long-rangedependent (LRD) traffic models. We review two such traffic models, ...

Gaussian Processes (GP) work well in the context of traffic count prediction, but cannot capitalize on the vast amount of data available in an entire city.

Dec 15, 2022 · Predictions for the missing values are generated from a Gaussian distribution, with a mean equal to the product of the weight matrix ...

Apr 7, 2024 · This article reviews existing literature on handling missing values. It compares and contrasts existing methods in terms of their ability to handle different ...

Firstly, the Gaussian process (GP) is used to model the observed traffic speed state. Such a stochastic process is further learned by the proposed AGNP ...

In this paper, we introduce a method that optimizes the execution of Decision Trees (DT). Decision Trees form the basis of many ensemble methods, such as Random ...

May 31, 2024 · Experimental results showed that the three models can improve the accuracy, reliability, and stability of missing value imputation greatly and ...