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Power System Transition Planning: An Industry-Aligned Framework for Long-Term Optimization
This work introduces the category of Power System Transition Planning optimization problem. It aims to shift power systems to …
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Causality-inspired Latent Feature Augmentation for Single Domain Generalization
Single domain generalization (Single-DG) intends to develop a generalizable model with only one single training domain to perform well …
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A GPU-Accelerated Moving-Horizon Algorithm for Training Deep Classification Trees on Large Datasets
Decision trees are essential yet NP-complete to train, prompting the widespread use of heuristic methods such as CART, which suffers …
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Bayesian optimization of separation gradients to maximize the performance of untargeted LC-MS
Liquid chromatography (LC) with gradient elution is a routine practice for separating complex chemical mixtures in mass spectrometry …
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A review of high-performance computing and parallel techniques applied to power systems optimization
The accelerating technological landscape and drive towards net-zero emission made the power system grow in scale and complexity. Serial …
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A sigmoidal approximation for chance-constrained nonlinear programs
We propose a sigmoidal approximation for the value-at-risk (that we call SigVaR) and we use this approximation to tackle nonlinear …
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