基本信息
views: 169
Career Trajectory
Bio
Prof Richtarik’s research interests lie at the intersection of mathematics, computer science, machine learning, optimization, numerical linear algebra, and high-performance computing. Through his work on randomized and distributed optimization algorithms, he has contributed to the foundations of machine learning, optimization and randomized numerical linear algebra. He is one of the original developers of Federated Learning – a new subfield of artificial intelligence whose goal is to train machine learning models over private data stored across a large number of heterogeneous devices, such as mobile phones or hospitals, in an efficient manner, and without compromising user privacy. In an October 2020 Forbes article, and alongside self-supervised learning and transformers, Federated Learning was listed as one of three emerging areas that will shape the next generation of Artificial Intelligence technologies.
Research Interests
Papers共 292 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2024)
Cited0Views0EIBibtex
0
0
arxiv(2024)
Cited0Views0Bibtex
0
0
arxiv(2024)
Cited0Views0Bibtex
0
0
AAAI 2024no. 18 (2024): 20344-20352
EUROPEAN JOURNAL OF APPLIED MATHEMATICSpp.1-24, (2024)
arxiv(2024)
Cited0Views0Bibtex
0
0
CoRR (2024)
Cited0Views0EIBibtex
0
0
arxiv(2024)
Cited0Views0Bibtex
0
0
CoRR (2024)
Cited0Views0EIBibtex
0
0
Load More
Author Statistics
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn