no code implementations • 14 Mar 2024 • Yuan Fang, Yipeng Liu, Jie Chen, Zhen Long, Ao Li, Chong-Yung Chi, Ce Zhu
In recent years, the fusion of high spatial resolution multispectral image (HR-MSI) and low spatial resolution hyperspectral image (LR-HSI) has been recognized as an effective method for HSI super-resolution (HSI-SR).
no code implementations • 30 Oct 2023 • Yiwei Li, Chien-Wei Huang, Shuai Wang, Chong-Yung Chi, Tony Q. S. Quek
Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients' data.
no code implementations • 26 Apr 2022 • Yiwei Li, Shuai Wang, Tsung-Hui Chang, Chong-Yung Chi
Specifically, we show that, by guaranteeing $(\epsilon, \delta)$-DP for each client per communication round, the proposed algorithm guarantees $(\mathcal{O}(q\epsilon \sqrt{p T}), \delta)$-DP after $T$ communication rounds while maintaining an $\mathcal{O}(1/\sqrt{pTQ})$ convergence rate for a convex and non-smooth learning problem, where $Q$ is the number of local SGD steps, $p$ is the client sampling probability, $q=\max_{i} q_i/\sqrt{1-q_i}$ and $q_i$ is the data sampling probability of each client under PCP.
no code implementations • 1 Apr 2020 • Amin Jalili, Chong-Yung Chi
Experimental results demonstrate that JPSD yields superior Emotion and AD recognition accuracy in comparison with the classical power spectral density (PSD) and graph PSD (GPSD) as the feature set for both applications.
no code implementations • 9 Aug 2017 • Chia-Hsiang Lin, Ruiyuan Wu, Wing-Kin Ma, Chong-Yung Chi, Yue Wang
This maximum volume inscribed ellipsoid (MVIE) idea has not been attempted in prior literature, and we show a sufficient condition under which the MVIE framework guarantees exact recovery of the factors.
no code implementations • 20 Jun 2014 • Chia-Hsiang Lin, Wing-Kin Ma, Wei-Chiang Li, Chong-Yung Chi, ArulMurugan Ambikapathi
In blind hyperspectral unmixing (HU), the pure-pixel assumption is well-known to be powerful in enabling simple and effective blind HU solutions.