Acm Transactions On Intelligent Systems And Technology

杂志介绍

Acm Transactions On Intelligent Systems And Technology杂志介绍

《Acm Transactions On Intelligent Systems And Technology》是一本以English为主的未开放获取国际优秀期刊，中文名称Acm 智能系统和技术交易，本刊主要出版、报道计算机科学-COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为7.2，最新CiteScore 指数为9.3。

本刊近期中国学者发表的论文主要有：

• No Free Lunch Theorem for Security and Utility in Federated Learning

  Author: Zhang, Xiaojin; Gu, Hanlin; Fan, Lixin; Chen, Kai; Yang, Qiang

• Self-supervised Discriminative Representation Learning by Fuzzy Autoencoder

  Author: Yang, Wenlu; Wang, Hongjun; Zhang, Yinghui; Liu, Zehao; Li, Tianrui

• A Query Optimizer for Range Queries over Multi-Attribute Trajectories

  Author: Xu, Jianqiu; Lu, Hua; Bao, Zhifeng

• Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend

  Author: Wu, Wendi; Li, Zongren; Zhao, Yawei; Yu, Chen; Zhao, Peilin; Liu, Ji; He, Kunlun

英文介绍

Acm Transactions On Intelligent Systems And Technology杂志英文介绍

ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world.

ACM TIST is published quarterly (six issues a year). Each issue has 8-11 regular papers, with around 20 published journal pages or 10,000 words per paper. Additional references, proofs, graphs or detailed experiment results can be submitted as a separate appendix, while excessively lengthy papers will be rejected automatically. Authors can include online-only appendices for additional content of their published papers and are encouraged to share their code and/or data with other readers.