2 citations · 4 across the 10 of their papers we have counts for
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cs.LG2024
Navigating Towards Fairness with Data Selection
Yixuan Zhang, Zhidong Li, Yang Wang +3
Machine learning algorithms often struggle to eliminate inherent data biases, particularly those arising from unreliable labels, which poses a significant challenge in ensuring fai…
stat.ML2024
Nonstationary Sparse Spectral Permanental Process
Zicheng Sun, Yixuan Zhang, Zenan Ling +2
Existing permanental processes often impose constraints on kernel types or stationarity, limiting the model's expressiveness. To overcome these limitations, we propose a novel appr…
cs.LG2024★ 2 cited
Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency
Yixuan Zhang, Feng Zhou
Fine-tuning pre-trained models is a widely employed technique in numerous real-world applications. However, fine-tuning these models on new tasks can lead to unfair outcomes. This…