8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping
Jia-Qi Yang, De-Chuan Zhan, Le Gan
Research has shown that deep networks tend to be overly optimistic about their predictions, leading to an underestimation of prediction errors. Due to the limited nature of data, e…
cs.LG2022
Avoid Overfitting User Specific Information in Federated Keyword Spotting
Xin-Chun Li, Jin-Lin Tang, Shaoming Song +5
Keyword spotting (KWS) aims to discriminate a specific wake-up word from other signals precisely and efficiently for different users. Recent works utilize various deep networks to…
cs.LG2021★ 8 cited
Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes
Xin-Chun Li, Le Gan, De-Chuan Zhan +3
Although federated learning (FL) has recently been proposed for efficient distributed training and data privacy protection, it still encounters many obstacles. One of these is the…