177 citations · 425 across the 19 of their papers we have counts for
20 papers
Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering
Chang Liu, Han Yu, Boyang Li +6
Noisy labels are commonly found in real-world data, which cause performance degradation of deep neural networks. Cleaning data manually is labour-intensive and time-consuming. Prev…
Noise-resistant Deep Metric Learning with Ranking-based Instance Selection
Chang Liu, Han Yu, Boyang Li +6
The existence of noisy labels in real-world data negatively impacts the performance of deep learning models. Although much research effort has been devoted to improving robustness…
Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection
Xu Guo, Boyang Li, Han Yu +1
The existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality. The adversarial neural transfer (ANT) framework utilize…
HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks
Yuanyuan Chen, Boyang Li, Han Yu +2
The behaviors of deep neural networks (DNNs) are notoriously resistant to human interpretations. In this paper, we propose Hypergradient Data Relevance Analysis, or HYDRA, which in…
Federated Crowdsensing: Framework and Challenges
Leye Wang, Han Yu, Xiao Han
Crowdsensing is a promising sensing paradigm for smart city applications (e.g., traffic and environment monitoring) with the prevalence of smart mobile devices and advanced network…
A VCG-based Fair Incentive Mechanism for Federated Learning
Mingshu Cong, Han Yu, Xi Weng +3
The enduring value of the Vickrey-Clarke-Groves (VCG) mechanism has been highlighted due to its adoption by Facebook ad auctions. Our research delves into its utility in the collab…