A Quantum-Inspired Direct Learning Strategy for Positive and Unlabeled Data

IF 2.5 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Computational Intelligence Systems Pub Date : 2023-12-01 DOI:10.1007/s44196-023-00373-9

Chenguang Zhang, Xuejiao Du, Yan Zhang

引用次数: 0

查看原文本刊更多论文

量子启发的正向和无标记数据直接学习策略

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Computational Intelligence Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

CiteScore

5.60

自引率

3.40%

发文量

审稿时长

10.5 months

期刊介绍： The International Journal of Computational Intelligence Systems publishes original research on all aspects of applied computational intelligence, especially targeting papers demonstrating the use of techniques and methods originating from computational intelligence theory. The core theories of computational intelligence are fuzzy logic, neural networks, evolutionary computation and probabilistic reasoning. The journal publishes only articles related to the use of computational intelligence and broadly covers the following topics: -Autonomous reasoning- Bio-informatics- Cloud computing- Condition monitoring- Data science- Data mining- Data visualization- Decision support systems- Fault diagnosis- Intelligent information retrieval- Human-machine interaction and interfaces- Image processing- Internet and networks- Noise analysis- Pattern recognition- Prediction systems- Power (nuclear) safety systems- Process and system control- Real-time systems- Risk analysis and safety-related issues- Robotics- Signal and image processing- IoT and smart environments- Systems integration- System control- System modelling and optimization- Telecommunications- Time series prediction- Warning systems- Virtual reality- Web intelligence- Deep learning