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cs.DC2024
Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients
Yan Li, Xiao Zhang, Mingyi Li +7
In this work, we study to release the potential of massive heterogeneous weak computing power to collaboratively train large-scale models on dispersed datasets. In order to improve…
cs.CV2024
CST: Calibration Side-Tuning for Parameter and Memory Efficient Transfer Learning
Feng Chen
Achieving a universally high accuracy in object detection is quite challenging, and the mainstream focus in the industry currently lies on detecting specific classes of objects. Ho…