Abstract: To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that ...

Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation. We also release a list of papers about transfer-based attacks here. If our paper or this code is ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...

Abstract: The prediction of pillar stability is of great importance because pillar failure can lead to large disasters. In this paper, a stochastic gradient boosting (SGB) model was applied to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

The statistical analysis of high-dimensional longitudinal data presents formidable challenges, primarily due to the dual complexity of managing intricate within-subject correlation patterns and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Ion exchange chromatography or ion chromatography (IC) is a ...

With the gradual increase in the grid-connected capacity of renewable energy sources, the uncertainty in the operation of power systems has increased, posing challenges to static security assessment ...

The search for a method to convert the discrete set of all synthesizable molecules to a continuous mathematical space, navigable through simple optimization procedures, has been at the forefront of ...