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07/20/2023
PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks
Collaborative inference has been a promising solution to enable resource...
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07/10/2023
Fed-CPrompt: Contrastive Prompt for Rehearsal-Free Federated Continual Learning
Federated continual learning (FCL) learns incremental tasks over time fr...
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01/08/2023
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices
In this work, we investigate the challenging problem of on-demand federa...
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08/15/2022
Energy and Spectrum Efficient Federated Learning via High-Precision Over-the-Air Computation
Federated learning (FL) enables mobile devices to collaboratively learn ...
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05/19/2022
Service Delay Minimization for Federated Learning over Mobile Devices
Federated learning (FL) over mobile devices has fostered numerous intrig...
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01/29/2022
Towards Fast and Accurate Federated Learning with non-IID Data for Cloud-Based IoT Applications
As a promising method of central model training on decentralized device ...
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11/11/2021
FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing
Federated learning (FL) enables devices in mobile edge computing (MEC) t...
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11/01/2021
To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices
Federated learning (FL), an emerging distributed machine learning paradi...
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01/13/2021
Towards Energy Efficient Federated Learning over 5G+ Mobile Devices
The continuous convergence of machine learning algorithms, 5G and beyond...
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12/22/2020
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
Recent advances in machine learning, wireless communication, and mobile ...
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12/21/2020
To Talk or to Work: Energy Efficient Federated Learning over Mobile Devices via the Weight Quantization and 5G Transmission Co-Design
Federated learning (FL) is a new paradigm for large-scale learning tasks...
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10/31/2020
Evaluation of Inference Attack Models for Deep Learning on Medical Data
Deep learning has attracted broad interest in healthcare and medical com...
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10/22/2020
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees
(Gradient) Expectation Maximization (EM) is a widely used algorithm for ...
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09/14/2020
Effective Proximal Methods for Non-convex Non-smooth Regularized Learning
Sparse learning is a very important tool for mining useful information a...
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08/11/2020
Towards Plausible Differentially Private ADMM Based Distributed Machine Learning
The Alternating Direction Method of Multipliers (ADMM) and its distribut...
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05/28/2020
Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks
Millimeter wave (mmWave) communications can potentially meet the high da...
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01/14/2020
Differentially Private and Fair Classification via Calibrated Functional Mechanism
Machine learning is increasingly becoming a powerful tool to make decisi...
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01/07/2019
Optimal Differentially Private ADMM for Distributed Machine Learning
Due to massive amounts of data distributed across multiple locations, di...
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08/21/2018
Resource Allocation for Cooperative D2D-Enabled Wireless Caching Networks
In this paper, we study the resource allocation problem for a cooperativ...
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01/13/2018
Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation
Secure communication is a promising technology for wireless networks bec...
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09/25/2017