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Found 5 papers, 1 papers with code
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization
This paper proposes a Parameter-efficient prompt Tuning approach with Adaptive Optimization, i. e., FedPepTAO, to enable efficient and effective FL of LLMs.
Accelerated Federated Learning with Decoupled Adaptive Optimization
The federated learning (FL) framework enables edge clients to collaboratively learn a shared inference model while keeping privacy of training data on clients.
Self-Supervised Bulk Motion Artifact Removal in Optical Coherence Tomography Angiography
With the structural information and appearance feature from noisy image as references, our model can remove larger BMA and produce better visualizing result.
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory
Despite achieving remarkable efficiency, traditional network pruning techniques often follow manually-crafted heuristics to generate pruned sparse networks.
Osteoporosis Prescreening using Panoramic Radiographs through a Deep Convolutional Neural Network with Attention Mechanism
The aim of this study was to investigate whether a deep convolutional neural network (CNN) with an attention module can detect osteoporosis on panoramic radiographs.
