Recently, a research team from the Rudolf Technology Center in Slovenia proposed a new method to optimize the sparse subgraph problem, which has wide applications in fields such as network analysis ...

The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid ...

Abstract: The iterative hard thresholding (IHT) algorithm is widely used for recovering sparse signals in compressed sensing. Despite the development of numerous variants of this effective algorithm, ...

Abstract: Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data can be ...