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cs.LG2026
Beyond What to Select: A Plug-and-play Oscillatory Data-Volume Scheduling for Efficient Model Training
Suorong Yang, Hanqi Zhu, Hai Gan +4
Data selection accelerates training by identifying representative training data while preserving model performance. However, existing methods mainly focus on designing sample-impor…
cs.LG2026
Data Agent: Learning to Select Data via End-to-End Dynamic Optimization
Suorong Yang, Fangjian Su, Hai Gan +5
Dynamic Data selection aims to accelerate training by prioritizing informative samples during online training. However, existing methods typically rely on task-specific handcrafted…
cs.LG2025
On-the-Fly Data Augmentation via Gradient-Guided and Sample-Aware Influence Estimation
Suorong Yang, Jie Zong, Lihang Wang +6
Data augmentation has been widely employed to improve the generalization of deep neural networks. Most existing methods apply fixed or random transformations. However, we find that…