Titlebook: Algorithms and Architectures for Parallel Processing; 22nd International C Weizhi Meng,Rongxing Lu,Jaideep Vaidya Conference proceedings 20

鑲嵌細(xì)工

防銹

pCOVID: A Privacy-Preserving COVID-19 Inference Framework,nts’ data privacy and model’s privacy while maintaining high accuracy and efficiency is widely considered a huge challenge. In this work, we propose a privacy-preserving COVID-19 inference framework based on a modified additive secret sharing scheme. Most of the prior works achieve the secure infere

CANE

含鐵

,Compromise Privacy in?Large-Batch Federated Learning via?Malicious Model Parameters,orks have shown that the server in FL can reveal user’s local data by inverting shared gradients. However, a large batchsize can defense against these attacks effectively by obfuscating gradients calculated on each data. In this paper, we propose a novel Gradient Inversion Attack which can compromis

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,PMemTrace: Lightweight and?Efficient Memory Access Monitoring for?Persistent Memory,arent crash consistency enforcement. However, traditional program analysis-oriented memory access monitoring mechanisms incur prohibitive performance overheads in persistent memory applications. Especially, for applications developed for systems with hybrid DRAM and persistent memory, existing memor

Biofeedback

雪崩

監(jiān)禁

啜泣

A Web Service Recommendation Method Based on Adaptive Gate Network and xDeepFM,al data or resources to the Internet in the form of Web services, resulting in an exponential increase in the number of Web services. To automatically generate or recommend a group of Web services according to the user‘s natural language requirements description, to build a Mashup application to mee

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