High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

Abstract: This study proposes a disaster rescue path optimization algorithm integrating dynamic programming and priority queue, and analyzes the impact of this algorithm on rescue efficiency under ...

Financial crime risk is not static. A customer’s risk profile can shift rapidly with new transactions, behaviors, or data. Yet historically, many financial institutions relied on one-time or ...

Genomics is playing an important role in transforming healthcare. Genetic data, however, is being produced at a rate that far outpaces Moore’s Law. Many efforts have been made to accelerate genomics ...

1 State Grid Jiangxi Electric Power Co., Ltd., Nanchang, China 2 State Key Laboratory of Advanced Electromagnetic Technology, Huazhong University of Science and Technology, Wuhan, China Large-scale ...

Abstract: Dynamic programming is one of the most challenging algorithm design techniques for computer programmers. Students frequently struggle with dynamic programming algorithms in Data Structures ...

Many important practical computations, such as scheduling, combinatorial, and optimization problems, use techniques known as integer programming to find the best combination of many variables. In ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...