This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
As renewable power rapidly reshapes global electricity systems, engineers face a growing challenge: how to operate increasingly complex grids with ...
The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
Abstract: This article proposes the row-stochastic event-based quantized (RSEQ) algorithm to address the distributed optimization problem with multiple communication constraints, including limited ...
With the increasing integration of a high proportion of renewable energy, the fluctuation characteristics of distributed power generation such as wind and photovoltaic energy affect the safe and ...
Abstract: This work develops and analyzes a class of adaptive biased stochastic optimization (ABSO) algorithms from the perspective of the GEneralized Adaptive gRadient (GEAR) method that contains ...
With the increasing penetration of electric vehicles (EVs) in road traffic, the spatial and temporal stochasticity of the travel pattern and charging demand of EVs as a mode of transportation and an ...
Change is the only constant in today’s rapidly evolving digital marketing landscape. Keeping up with the latest innovations isn’t just a choice – it’s a necessity for survival. Generative engine ...
ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...
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