no code implementations • 4 Mar 2024 • Ying-Hsuan Wu, Jun-Wei Hsieh, Li Xin, Shin-You Teng, Yi-Kuan Hsieh, Ming-Ching Chang
In the second stage, our label refurbishment method is applied to obtain soft labels for multi-expert ensemble learning, providing a principled solution to the long-tail noisy label problem.
no code implementations • 28 Dec 2023 • Yi-Kuan Hsieh, Jun-Wei Hsieh, Yu-Chee Tseng, Ming-Ching Chang, Li Xin
Furthermore, the use of a fixed Gaussian kernel fails to account for the varying pixel distribution with respect to the camera distance.
1 code implementation • PAMI 2023 • Lu Xiaotong, Dong Weisheng, Li Xin, Wu Jinjian, Li Leida, Shi Guangming
Using pruning as a search strategy, we advocate three new insights for network engineering: 1) to formulate adaptive search as a cold start strategy to find a compact subnetwork on the coarse scale; and 2) to automatically learn the threshold for network pruning; 3) to offer flexibility to choose between efficiency and robustness .