214 citations · 214 across the 4 of their papers we have counts for
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cs.LG2026
PowerStep: Memory-Efficient Adaptive Optimization via -Norm Steepest Descent
Yao Lu, Dengdong Fan, Shixun Zhang +1
Adaptive optimizers such as Adam are standard for training Transformers, but storing gradient first and second moments incurs substantial memory overhead. We introduce PowerStep, a…
cs.LG2025
Calibrating and Rotating: A Unified Framework for Weight Conditioning in PEFT
Da Chang, Peng Xue, Yu Li +3
Parameter-Efficient Fine-Tuning (PEFT) methods are crucial for adapting large pre-trained models. Among these, LoRA is considered a foundational approach. Building on this, the inf…
cs.LG2020★ 214 cited
FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC
Rongfei Zeng, Shixun Zhang, Jiaqi Wang +1
Promising federated learning coupled with Mobile Edge Computing (MEC) is considered as one of the most promising solutions to the AI-driven service provision. Plenty of studies foc…