no code implementations • 18 Sep 2023 • Sina Aeeneh, Nikola Zlatanov, Jiangshan Yu
In this paper, we derive a new upper bound on the accuracy of the MVF for the multi-class classification problem.
no code implementations • 22 Dec 2022 • Yuanzhe Zhang, Shirui Pan, Jiangshan Yu
Blockchain sharding is a promising approach to this problem.
no code implementations • 28 Nov 2021 • Chaochen Shi, Yong Xiang, Jiangshan Yu, Longxiang Gao
To make the model more focused on the key contextual information, we use a multi-head attention network to generate embeddings for code features.
no code implementations • 31 May 2021 • Chaochen Shi, Yong Xiang, Robin Ram Mohan Doss, Jiangshan Yu, Keshav Sood, Longxiang Gao
Our experimental studies on over 3, 300 real-world Ethereum smart contracts show that our model can classify smart contracts without source code and has better performance than baseline models.
no code implementations • 18 Jul 2020 • Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma
This paper firstly considers the research problem of fairness in collaborative deep learning, while ensuring privacy.
1 code implementation • 4 Jun 2019 • Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng
This problem can be addressed by either a centralized framework that deploys a central server to train a global model on the joint data from all parties, or a distributed framework that leverages a parameter server to aggregate local model updates.