Abstract Gaussian Process Latent Variable Model (GPLVM), as a flexible bayesian non-
parametric modeling method, has been extensively studied and applied in many learning …

Abstract In 2007, Labeled Faces in the Wild was released in an effort to spur research in
face recognition, specifically for the problem of face verification with unconstrained images …

Face verification remains a challenging problem in very complex conditions with large
variations such as pose, illumination, expression, and occlusions. This problemis …

Abstract State-of-Health (SOH) estimation is crucial for the safety and reliability of battery-
based applications. Data-driven methods have shown their promising potential in battery …

Gaussian process models (GPMs) are widely regarded as a prominent tool for learning
statistical data models that enable interpolation, regression, and classification. These …

Even if you have spent some time reading about machine learning, chances are that you
have never heard of Gaussian processes. And if you have, rehearsing the basics is always a …

Probably the most important technological invention of the previous century was the
transistor. And another very important invention was the digital computer, which got a …

Traditional anomaly detection procedures assume that normal observations are obtained
from a single distribution. However, due to the complexities of modern industrial processes …

Memory-based collaborative filtering (CF) makes recommendations based on a collection of
user preferences for items. The idea underlying this approach is that the interests of an …

Regression modelling has always been a key process in unlocking the relationships
between independent and dependent variables that are held within data. In recent years …