no code implementations • 10 Dec 2023 • Hye-Bin Shin, Kang Yin, Seong-Whan Lee
In the quest for efficient neural network models for neural data interpretation and user intent classification in brain-computer interfaces (BCIs), learning meaningful sparse representations of the underlying neural subspaces is crucial.
no code implementations • 18 Aug 2023 • Beichuan Zhang, Chenggen Sun, Jianchao Tan, Xinjun Cai, Jun Zhao, Mengqi Miao, Kang Yin, Chengru Song, Na Mou, Yang song
Increasing the size of embedding layers has shown to be effective in improving the performance of recommendation models, yet gradually causing their sizes to exceed terabytes in industrial recommender systems, and hence the increase of computing and storage costs.
no code implementations • 24 Nov 2022 • Kang Yin, Byeong-Hoo Lee, Byoung-Hee Kwon, Jeong-Hyun Cho
In this paper, we propose a target-centered subject transfer framework as a data augmentation approach.
1 code implementation • 26 Nov 2021 • Xie Zhang, Chengpei Tang, Yasong An, Kang Yin
Then, for solving the imbalance issue, the extracted common feature in Wimuse is encouraged to get close to the counterpart features of the STS models.