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cs.LG2026
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
Kumar Shubham, Pavan Karjol, Kiran M K +1
The performance of machine learning models often relies on large labeled datasets; however, data collected from diverse sources can contain label noise. Recent work has shown that,…
cs.LG2024
Boosting Gradient Ascent for Continuous DR-submodular Maximization
Qixin Zhang, Zongqi Wan, Zengde Deng +4
Projected Gradient Ascent (PGA) is the most commonly used optimization scheme in machine learning and operations research areas. Nevertheless, numerous studies and examples have sh…