Search Results - "Ren, Xuebin"

Author Correction: Quantum-aided secure deep neural network inference on real quantum computers by Yu, Hanqiao, Ren, Xuebin, Zhao, Cong, Yang, Shusen, McCann, Julie

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Quantum-aided secure deep neural network inference on real quantum computers by Yu, Hanqiao, Ren, Xuebin, Zhao, Cong, Yang, Shusen, McCann, Julie

“…Deep neural networks (DNNs) are phenomenally successful machine learning methods broadly applied to many different disciplines. However, as complex two-party…”
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Impact of Prior Knowledge and Data Correlation on Privacy Leakage: A Unified Analysis by Li, Yanan, Ren, Xuebin, Yang, Shusen, Yang, Xinyu

“…It has been widely understood that differential privacy can guarantee rigorous privacy against adversaries with arbitrary prior knowledge. However, recent…”
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On Binary Decomposition Based Privacy-Preserving Aggregation Schemes in Real-Time Monitoring Systems by Yang, Xinyu, Ren, Xuebin, Lin, Jie, Yu, Wei

“…In real-time monitoring systems, fine-grained measurements would pose great privacy threats to the participants as real-time measurements could disclose…”
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A Zeroth-Order Adaptive Learning Rate Method to Reduce Cost of Hyperparameter Tuning for Deep Learning by Li, Yanan, Ren, Xuebin, Zhao, Fangyuan, Yang, Shusen

“…Due to powerful data representation ability, deep learning has dramatically improved the state-of-the-art in many practical applications. However, the utility…”
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p-Power Exponential Mechanisms for Differentially Private Machine Learning by Li, Yanan, Ren, Xuebin, Zhao, Fangyuan, Yang, Shusen

“…Differentially private stochastic gradient descent (DP-SGD) that perturbs the clipped gradients is a popular approach for private machine learning. Gaussian…”
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textsf : High-Dimensional Crowdsourced Data Publication With Local Differential Privacy by Xuebin Ren, Chia-Mu Yu, Weiren Yu, Shusen Yang, Xinyu Yang, McCann, Julie A., Yu, Philip S.

“…High-dimensional crowdsourced data collected from numerous users produces rich knowledge about our society; however, it also brings unprecedented privacy…”
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On binary decomposition based privacy-preserving aggregation schemes in real-time monitoring systems by Xuebin Ren, Xinyu Yang, Jie Lin, Wei Yu

“…Real-time monitoring systems can introduce numerous benefits to the participants in terms of performing data mining and analysis. Nonetheless, due to the…”
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On Scaling Perturbation Based Privacy-Preserving Schemes in Smart Metering Systems by Xuebin Ren, Xinyu Yang, Jie Lin, Qingyu Yang, Wei Yu

“…The smart grid poses great concern about the exposure of consumers' privacy as the fine-grained measurements in the smart metering system can expose consumer's…”
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Towards Efficient and Stable K-Asynchronous Federated Learning With Unbounded Stale Gradients on Non-IID Data by Zhou, Zihao, Li, Yanan, Ren, Xuebin, Yang, Shusen

“…Federated learning (FL) is an emerging privacy-preserving paradigm that enables multiple participants collaboratively to train a global model without uploading…”
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Multi-stage Asynchronous Federated Learning with Adaptive Differential Privacy by Li, Yanan, Yang, Shusen, Ren, Xuebin, Shi, Liang, Zhao, Cong

“…The fusion of federated learning and differential privacy can provide more comprehensive and rigorous privacy protection, thus attracting extensive interests…”
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FedGen: Personalized federated learning with data generation for enhanced model customization and class imbalance by Zhao, Peng, Guo, Shaocong, Li, Yanan, Yang, Shusen, Ren, Xuebin

“…Federated learning has emerged as a prominent solution for the collaborative training of machine learning models without exchanging local data. However,…”
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Copula-Based Multi-Dimensional Crowdsourced Data Synthesis and Release with Local Privacy by Xinyu Yang, Teng Wang, Xuebin Ren, Wei Yu

“…Various paradigms, based on differential privacy, have been proposed to release a privacy-preserving dataset with statistical approximation. Nonetheless, most…”
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Locally Private High-Dimensional Crowdsourced Data Release Based on Copula Functions by Wang, Teng, Yang, Xinyu, Ren, Xuebin, Yu, Wei, Yang, Shusen

“…With the increasing popularity of crowdsourcing services, high-dimensional crowdsourced data provides a wealth of knowledge. Nonetheless, unprecedented privacy…”
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A personalized cross-domain recommendation with federated meta learning by Zhao, Peng, Jin, Yuanyang, Ren, Xuebin, Li, Yanan

“…Cross-domain Recommendation (CDR) is an effective method for solving the cold-start problem in traditional recommendation systems. This technique transfers…”
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MPCSM: Microservice Placement for Edge-Cloud Collaborative Smart Manufacturing by Wang, Yimeng, Zhao, Cong, Yang, Shusen, Ren, Xuebin, Wang, Luhui, Zhao, Peng, Yang, Xinyu

“…Latency-aware service placement is promising in reducing the overall service response latency of proliferating edge-cloud collaborative smart manufacturing…”
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Survey on Improving Data Utility in Differentially Private Sequential Data Publishing by Yang, Xinyu, Wang, Teng, Ren, Xuebin, Yu, Wei

“…The massive generation, extensive sharing, and deep exploitation of data in the big data era have raised unprecedented privacy threats. To address privacy…”
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RTCoInfer: Real-time Collaborative CNN Inference for Stream Analytics on Ubiquitous Images by Zhang, Zhanhua, Yang, Shusen, Zhao, Cong, Ren, Xuebin, Yu, Hanqiao, Han, Qing, Guo, Siyan

“…Emerging intelligent applications based on accurate and timely stream analytics require real-time CNN inference of massive data continuously generated at the…”
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IndustEdge: A Time-Sensitive Networking Enabled Edge-Cloud Collaborative Intelligent Platform for Smart Industry by Wang, Yimeng, Yang, Shusen, Ren, Xuebin, Zhao, Peng, Zhao, Cong, Yang, Xinyu

“…An edge-cloud collaborative intelligent (ECCI) platform is of great significance for the agile development and rapid deployment of ECCI applications, which are…”
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FedLED: Label-Free Equipment Fault Diagnosis With Vertical Federated Transfer Learning by Shen, Jie, Yang, Shusen, Zhao, Cong, Ren, Xuebin, Zhao, Peng, Yang, Yuqian, Han, Qing, Wu, Shuaijun

“…Intelligent equipment fault diagnosis based on federated transfer learning (FTL) attracts considerable attention from both academia and industry. It allows…”
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