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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: Multivariate time series (MTS) forecasting presents significant challenges due to the diverse noise distributions and complex periodic patterns across different channels. Existing ...
Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...
Abstract: Motivated by diverse secure requirements of multiuser in unmanned aerial vehicle (UAV) systems, we propose a collaborative secret and covert transmission method for multi-antenna ground ...
Abstract: Large language models (LLMs) have garnered unprecedented advancements across diverse fields, ranging from natural language processing to computer vision and beyond. The prowess of LLMs is ...
Abstract: This paper proposes a novel distributionally robust energy and reserve dispatch model with distributed renewable predictions. Through leveraging the prediction information from both the ...
Abstract: This paper presents a hybrid Energy Storage System (ESS) for DC microgrids, highlighting its potential for supporting future grid functions with high Renewable Energy Sources (RESs) ...
Abstract: Velostat is a conductive material that can be used as sensing media for robotic tactile perception. However, the performance of the Velostat-based sensors is suppressed by its intrinsic ...
Abstract: The adoption of voluntary environmental standards has emerged as a promising approach to coping with climate change and achieving sustainable development. While prior research has ...