Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...

Abstract: Online learning is a well established learning paradigm which has both theoretical and practical appeals. The goal of online learning is to make a sequence of accurate predictions given ...

Abstract: Proximal Algorithms discusses proximal operators and proximal algorithms, and illustrates their applicability to standard and distributed convex optimization in general and many applications ...

Abstract: Electronic Design Automation (EDA) in analog Integrated Circuits (ICs) has been the focus of extensive research; however, unlike its digital counterpart, it has not achieved widespread ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6221036 ...

Abstract: Optical coherence tomography angiography has transformed retinal vascular imaging by providing non-invasive, high-resolution visualization. However, achieving an optimal balance between ...

Abstract: Novel sensing and communication techniques have created new opportunities for unobtrusive vital sign monitoring. Due to the features of wireless power and data transfer and non-line-of-sight ...

Abstract: The technology of electric propulsion aircraft (EPA) represents an important direction and an advanced stage in the development of aviation electrification. It is a key pathway for green ...

Abstract: This paper explores the integration of Artificial Intelligence into 6G networks, focusing on optimizing communication, resource allocation, and enhancing security. As communication systems ...

Abstract: Due to the wide existence of unlabeled graph-structured data (e.g. molecular structures), the graph-level clustering has recently attracted increasing attention, whose goal is to divide the ...

Abstract: This paper proposes a deep reinforcement learning scheme for the primary frequency response of floating offshore wind turbines (FOWTs). Considering the fact that current FOWT simulators ...

Abstract: Deep learning offers efficient solutions for drug-target interaction prediction, but current methods often fail to capture the full complexity of multi-modal data (i.e. sequence, graphs, and ...