Driven by the upcoming development of the sixth-generation communication system (6G),
the distributed machine learning schemes represented by federated learning has shown …

Due to the excellent energy-saving and environmental protection features, electric vehicles
(EVs) are gaining significant market penetration, especially in densely populated urban …

An improved Adam optimization algorithm combining adaptive coefficients and composite
gradients based on randomized block coordinate descent is proposed to address issues of …

High-dimensional and sparse (HiDS) matrices are frequently adopted to describe the
complex relationships in various big data-related systems and applications. A Position …

Drought is one of the major global natural disasters, and appropriate monitoring systems are
essential to reveal drought trends. In this regard, deep learning is a very promising approach …

The optimization of operating conditions in the polyester polymerization process is crucial for
enhancing the quality of the resulting polyester. A novel multi-objective optimization …

Many problems in the Internet of Things (IoT) can be regarded as online optimization
problems. For this reason, an online-constrained problem in IoT is considered in this article …

The machine learning community has witnessed impressive advancements since the first
appearance of large language models (LLMs), yet their huge memory consumption has …

目前深度学习技术发展快速, 针对其在短期负荷预测任务中处理离散数据效果较差以及泛化性不
佳的问题, 提出一种基于注意力机制的长短期记忆网络(longshort …

Background Orphan gene play an important role in the environmental stresses of many
species and their identification is a critical step to understand biological functions. Moso …