1 code implementation • 31 Oct 2023 • Zixin Wang, Yadan Luo, Liang Zheng, Zhuoxiao Chen, Sen Wang, Zi Huang
In this paper, we present a comprehensive survey on online test-time adaptation (OTTA), a paradigm focused on adapting machine learning models to novel data distributions upon batch arrival.
1 code implementation • 16 Oct 2023 • Zhuoxiao Chen, Yadan Luo, Zixin Wang, Zijian Wang, Xin Yu, Zi Huang
To seek effective solutions, we investigate a more practical yet challenging research task: Open World Active Learning for 3D Object Detection (OWAL-3D), aiming at selecting a small number of 3D boxes to annotate while maximizing detection performance on both known and unknown classes.
1 code implementation • 6 Aug 2023 • Zixin Wang, Yadan Luo, Zhi Chen, Sen Wang, Zi Huang
The prevalence of domain adaptive semantic segmentation has prompted concerns regarding source domain data leakage, where private information from the source domain could inadvertently be exposed in the target domain.
no code implementations • 3 Jan 2023 • Yandong Shi, Lixiang Lian, Yuanming Shi, Zixin Wang, Yong Zhou, Liqun Fu, Lin Bai, Jun Zhang, Wei zhang
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from "connected things" to "connected intelligence", featured by ultra high density, large-scale, dynamic heterogeneity, diversified functional requirements and machine learning capabilities, which leads to a growing need for highly efficient intelligent algorithms.
no code implementations • 13 Aug 2022 • Zhanpeng Yang, Yuanming Shi, Yong Zhou, Zixin Wang, Kai Yang
In this paper, we shall propose a decentralized blockchain based FL (B-FL) architecture by using a secure global aggregation algorithm to resist malicious devices, and deploying practical Byzantine fault tolerance consensus protocol with high effectiveness and low energy consumption among multiple edge servers to prevent model tampering from the malicious server.
1 code implementation • 11 Jul 2022 • Zixin Wang, Yadan Luo, Peng-Fei Zhang, Sen Wang, Zi Huang
A typical multi-source domain adaptation (MSDA) approach aims to transfer knowledge learned from a set of labeled source domains, to an unlabeled target domain.
no code implementations • 28 Mar 2022 • Yinan Zou, Zixin Wang, Xu Chen, Haibo Zhou, Yong Zhou
Based on the convergence analysis, we formulate an optimization problem to minimize the upper bound to enhance the learning performance, followed by proposing an alternating optimization algorithm to facilitate the optimal transceiver design for AirComp-assisted FL.
no code implementations • 22 Dec 2020 • Shiqi Sheng, Haijun Yang, Liuhua Mu, Zixin Wang, Jihong Wang, Peng Xiu, Jun Hu, Xin Zhang, Feng Zhang, Haiping Fang
We experimentally demonstrated that the AYFFF self-assemblies adsorbed with various monovalent cations (Na+, K+, and Li+) show unexpectedly super strong paramagnetism.
Biological Physics