Titlebook: Algorithms and Architectures for Parallel Processing; 23rd International C Zahir Tari,Keqiu Li,Hongyi Wu Conference proceedings 2024 The Ed

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,Differential Privacy in Federated Dynamic Gradient Clipping Based on Gradient Norm,y affecting the accuracy of models. However, the imprecise clipped threshold affects the amount of gradient noise leading to degradation of model accuracy. In this paper, for reducing the impact of gradient noise on model accuracy, we propose a differential privacy in federated dynamic gradient clip

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,SolGPT: A GPT-Based Static Vulnerability Detection Model for Enhancing Smart Contract Security,acts, particularly those written in Solidity, the predominant language for smart contracts. Conventional deep learning methodologies largely rely on an abundant pool of labeled training instances, a resource that remains scarce in the domain, thereby limiting the efficacy of vulnerability detection.

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,Distributed Task Offloading Method Based on Federated Reinforcement Learning in Vehicular Networks er of vehicles, many tasks cannot be completed within specified time. The task offloading method based on mobile edge computing (MEC) effectively solves the problem. However, the existing research does not fully consider user needs and has the disadvantages of limited application scope and slow trai

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,A Hybrid Active and Passive Cache Method Based on Deep Learning in Edge Computing, quality of experience (QoE) has become a major challenge for Internet service providers (ISPs). To alleviate the burden of Internet traffic, we propose a hybrid active-passive cache update strategy. For newly released micro-videos, the multimodal transformer popularity prediction model (MTPP) is us

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