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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: Building the next-generation wireless systems that could support services such as the metaverse, digital twins (DTs), and holographic teleportation is challenging to achieve exclusively ...
Abstract: Data-driven methods, especially reinforcement learning (RL), are adept at addressing uncertainties but are poor at ensuring safety, which is a critical requirement in active distribution ...
Abstract: Multiview subspace clustering (MSC) maximizes the utilization of complementary description information provided by multiview data and achieves impressive clustering performance. However, ...
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 ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6221021 ...
Distributionally Robust Energy and Reserve Dispatch with Distributed Predictions of Renewable Energy
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 article highlights the critical role of reliable dc-dc converter operation in ensuring the stability of power conversion systems, especially in extreme environments like underwater ...
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: 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) ...
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