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Communication-Efficient Edge AI: Algorithms and Systems
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A Mathematical Theory of Communication
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Random Gradient-Free Minimization of Convex Functions
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Network Offloading Policies for Cloud Robotics: A Learning-Based Approach
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Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms
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Distributed quantized gradient-free algorithm for multi-agent convex optimization
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Communication-efficient algorithms for statistical optimization
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Exact Convergence of Gradient-Free Distributed Optimization Method in a Multi-Agent System
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Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach
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A Survey on Mobile Edge Computing: The Communication Perspective
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Fast ConvNets Using Group-Wise Brain Damage
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Quantized Convolutional Neural Networks for Mobile Devices
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NON-ASYMPTOTIC RATES FOR COMMUNICATION EFFICIENT DISTRIBUTED ZEROTH ORDER STRONGLY CONVEX OPTIMIZATION
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High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning
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Speech recognition with deep recurrent neural networks
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Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets
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A hybrid approach to offloading mobile image classification
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Pliable Data Shuffling for On-device Distributed Learning
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Layer-wise Deep Neural Network Pruning via Iteratively Reweighted Optimization
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Distributed Deep Learning Strategies for Automatic Speech Recognition
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Deep Joint Source-Channel Coding of Images with Feedback
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Hierarchical Federated Learning ACROSS Heterogeneous Cellular Networks
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Client-Edge-Cloud Hierarchical Federated Learning
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An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections
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BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems
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Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
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SystemML: Declarative machine learning on MapReduce
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BranchyNet: Fast inference via early exiting from deep neural networks
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Communication-constrained multi-AUV cooperative SLAM
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Fundamental Limits of Wireless Distributed Computing Networks
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The Role of Network Topology for Distributed Machine Learning
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Improving Device-Edge Cooperative Inference of Deep Learning via 2-Step Pruning
inferredcites →https://doi.org/10.1109/ipdpsw.2018.00137openalex-snapshot
Near-Optimal Straggler Mitigation for Distributed Gradient Methods
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Communication constrained cloud-based long-term visual localization in real time
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A pliable index coding approach to data shuffling
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Coded Distributed Computing with Node Cooperation Substantially Increases Speedup Factors
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Improving Distributed Gradient Descent Using Reed-Solomon Codes
inferredcites →https://doi.org/10.1109/isit.2018.8437709openalex-snapshot
Wireless MapReduce Distributed Computing
inferredcites →https://doi.org/10.1109/isit.2018.8437860openalex-snapshot
Coded Computing for Distributed Graph Analytics
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Robust Gradient Descent via Moment Encoding and LDPC Codes
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Distributed Stochastic Gradient Descent Using LDGM Codes
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Fitting ReLUs via SGD and Quantized SGD
inferredcites →https://doi.org/10.1109/isit.2019.8849684openalex-snapshot
Speeding Up Distributed Gradient Descent by Utilizing Non-persistent Stragglers
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Stochastic Gradient Coding for Flexible Straggler Mitigation in Distributed Learning
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MIMO Over-the-Air Computation for High-Mobility Multimodal Sensing
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Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract Theory
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Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
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Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence
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Efficient Processing of Deep Neural Networks: A Tutorial and Survey
inferredcites →https://doi.org/10.1109/jproc.2018.2817461openalex-snapshot
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization
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Tactile Robots as a Central Embodiment of the Tactile Internet
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Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
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Mobile Edge Intelligence and Computing for the Internet of Vehicles
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An overview of limited feedback in wireless communication systems
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Multi-Cell MIMO Cooperative Networks: A New Look at Interference
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Adaptive Federated Learning in Resource Constrained Edge Computing Systems
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Stochastic Gradient Coding for Straggler Mitigation in Distributed Learning
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A Node-Selection-Based Sub-Task Assignment Method for Coded Edge Computing
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On Model Coding for Distributed Inference and Transmission in Mobile Edge Computing Systems
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Toward an Intelligent Edge: Wireless Communication Meets Machine Learning
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Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network
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Toward a theory of in-network computation in wireless sensor networks
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Coding for Distributed Fog Computing
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When Mobile Blockchain Meets Edge Computing
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The Roadmap to 6G: AI Empowered Wireless Networks
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SecureBoost: A Lossless Federated Learning Framework
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Secure Distributed On-Device Learning Networks with Byzantine Adversaries
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Deep Reinforcement Learning: A Brief Survey
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Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges
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Federated Learning: Challenges, Methods, and Future Directions
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Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI
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ZONE: Zeroth-Order Nonconvex Multiagent Optimization Over Networks
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Cloud-Based Collaborative 3D Mapping in Real-Time With Low-Cost Robots
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Petuum: A New Platform for Distributed Machine Learning on Big Data
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DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters
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Reconfigurable Intelligent Surface for Green Edge Inference
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Computation Over Multiple-Access Channels
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Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations
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Speeding Up Distributed Machine Learning Using Codes
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A Fundamental Tradeoff Between Computation and Communication in Distributed Computing
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Near Optimal Coded Data Shuffling for Distributed Learning
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A Scalable Framework for Wireless Distributed Computing
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Randomized Gradient-Free Method for Multiagent Optimization Over Time-Varying Networks
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Zeroth-Order Method for Distributed Optimization With Approximate Projections
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Learning Separable Filters
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Harnessing Interference for Analog Function Computation in Wireless Sensor Networks
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Variance-Reduced Stochastic Learning by Networked Agents Under Random Reshuffling
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Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization
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Blind Over-the-Air Computation and Data Fusion via Provable Wirtinger Flow
inferredcites →https://doi.org/10.1109/tsp.2020.2971203openalex-snapshot
Distributed Sensing With Orthogonal Multiple Access: To Code or not to Code?
inferredcites →https://doi.org/10.1109/tsp.2020.2981904openalex-snapshot
Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air
inferredcites →https://doi.org/10.1109/twc.2019.2946140openalex-snapshot
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
inferredcites →https://doi.org/10.1109/twc.2019.2946245openalex-snapshot
Broadband Analog Aggregation for Low-Latency Federated Edge Learning
inferredcites →https://doi.org/10.1109/twc.2019.2961673openalex-snapshot
Federated Learning via Over-the-Air Computation
inferredcites →https://doi.org/10.1109/twc.2019.2963654openalex-snapshot
NOMA-Enhanced Computation Over Multi-Access Channels
inferredcites →https://doi.org/10.1109/twc.2020.2974748openalex-snapshot
Federated Learning Over Wireless Fading Channels
inferredcites →https://doi.org/10.1109/twc.2020.3024629openalex-snapshot
A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks
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Energy Efficient Federated Learning Over Wireless Communication Networks
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One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis
inferredcites →https://doi.org/10.1137/1.9780898718768openalex-snapshot
Introduction to Derivative-Free Optimization
inferredcites →https://doi.org/10.1137/140954362openalex-snapshot
A Stochastic Quasi-Newton Method for Large-Scale Optimization
inferredcites →https://doi.org/10.1145/2939672.2939839openalex-snapshot
Compressing Convolutional Neural Networks in the Frequency Domain
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3154503openalex-snapshot
Distributed Statistical Machine Learning in Adversarial Settings
inferredcites →https://doi.org/10.1145/3219617.3219655openalex-snapshot
Distributed Statistical Machine Learning in Adversarial Settings
inferredcites →https://doi.org/10.1145/3286062.3286070openalex-snapshot
Neural Networks Meet Physical Networks
inferredcites →https://doi.org/10.1145/3358205openalex-snapshot
Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT
inferredcites →https://doi.org/10.1145/3363554openalex-snapshot
Scalable Deep Learning on Distributed Infrastructures
inferredcites →https://doi.org/10.1145/956750.956776openalex-snapshot
Privacy-preserving k -means clustering over vertically partitioned data
inferredcites →https://doi.org/10.1146/annurev-control-053018-023825openalex-snapshot
A Tour of Reinforcement Learning: The View from Continuous Control
inferredcites →https://doi.org/10.1177/0141076818815510openalex-snapshot
Artificial intelligence-enabled healthcare delivery
inferredcites →https://doi.org/10.13016/m2cl1x-yatqopenalex-snapshot
ELASTIC GOSSIP: DISTRIBUTING NEURAL NETWORK TRAINING USING GOSSIP-LIKE PROTOCOLS
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Predicting parameters in deep learning
inferredcites →https://doi.org/10.1609/aaai.v32i1.11728openalex-snapshot
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training
inferredcites →https://doi.org/10.21437/interspeech.2014-274openalex-snapshot
1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs
inferredcites →https://doi.org/10.21437/interspeech.2015-354openalex-snapshot
Scalable distributed DNN training using commodity GPU cloud computing
inferredcites →https://doi.org/10.23919/date.2017.7927211openalex-snapshot
MoDNN: Local distributed mobile computing system for Deep Neural Network
inferredcites →https://doi.org/10.24963/ijcai.2018/447openalex-snapshot
On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization
inferredcites →https://doi.org/10.3390/e22050544openalex-snapshot
Straggler-Aware Distributed Learning: Communication–Computation Latency Trade-Off
inferredcites →https://doi.org/10.48550/arxiv.1306.0543openalex-snapshot
Predicting Parameters in Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1312.7853openalex-snapshot
Communication Efficient Distributed Optimization using an Approximate Newton-type Method
inferredcites →https://doi.org/10.48550/arxiv.1404.0736openalex-snapshot
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
inferredcites →https://doi.org/10.48550/arxiv.1409.1458openalex-snapshot
Communication-Efficient Distributed Dual Coordinate Ascent
inferredcites →https://doi.org/10.48550/arxiv.1411.0347openalex-snapshot
Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares
inferredcites →https://doi.org/10.48550/arxiv.1412.6115openalex-snapshot
Compressing Deep Convolutional Networks using Vector Quantization
inferredcites →https://doi.org/10.48550/arxiv.1502.02551openalex-snapshot
Deep Learning with Limited Numerical Precision
inferredcites →https://doi.org/10.48550/arxiv.1504.04788openalex-snapshot
Compressing Neural Networks with the Hashing Trick
inferredcites →https://doi.org/10.48550/arxiv.1506.01900openalex-snapshot
Communication Complexity of Distributed Convex Learning and Optimization
inferredcites →https://doi.org/10.48550/arxiv.1508.02087openalex-snapshot
A Linearly-Convergent Stochastic L-BFGS Algorithm
inferredcites →https://doi.org/10.48550/arxiv.1510.00149openalex-snapshot
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
inferredcites →https://doi.org/10.48550/arxiv.1510.01722openalex-snapshot
Structured Transforms for Small-Footprint Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1511.00363openalex-snapshot
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
inferredcites →https://doi.org/10.48550/arxiv.1511.03575openalex-snapshot
Federated Optimization:Distributed Optimization Beyond the Datacenter
inferredcites →https://doi.org/10.48550/arxiv.1602.02830openalex-snapshot
Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
inferredcites →https://doi.org/10.48550/arxiv.1602.05629openalex-snapshot
Communication-Efficient Learning of Deep Networks from Decentralized Data
inferredcites →https://doi.org/10.48550/arxiv.1610.02132openalex-snapshot
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
inferredcites →https://doi.org/10.48550/arxiv.1610.05492openalex-snapshot
Federated Learning: Strategies for Improving Communication Efficiency
inferredcites →https://doi.org/10.48550/arxiv.1611.00429openalex-snapshot
Distributed Mean Estimation with Limited Communication
inferredcites →https://doi.org/10.48550/arxiv.1611.04581openalex-snapshot
How to scale distributed deep learning?
inferredcites →https://doi.org/10.48550/arxiv.1611.09726openalex-snapshot
Gossip training for deep learning
inferredcites →https://doi.org/10.48550/arxiv.1702.04008openalex-snapshot
Soft Weight-Sharing for Neural Network Compression
inferredcites →https://doi.org/10.48550/arxiv.1702.08169openalex-snapshot
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
inferredcites →https://doi.org/10.48550/arxiv.1705.08665openalex-snapshot
Bayesian Compression for Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1706.02677openalex-snapshot
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
inferredcites →https://doi.org/10.48550/arxiv.1706.04972openalex-snapshot
Device Placement Optimization with Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1710.09854openalex-snapshot
Gradient Sparsification for Communication-Efficient Distributed Optimization
inferredcites →https://doi.org/10.48550/arxiv.1711.10677openalex-snapshot
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
inferredcites →https://doi.org/10.48550/arxiv.1712.01887openalex-snapshot
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
inferredcites →https://doi.org/10.48550/arxiv.1802.03475openalex-snapshot
Communication-Computation Efficient Gradient Coding
inferredcites →https://doi.org/10.48550/arxiv.1802.05799openalex-snapshot
Horovod: fast and easy distributed deep learning in TensorFlow
inferredcites →https://doi.org/10.48550/arxiv.1803.05880openalex-snapshot
GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent
inferredcites →https://doi.org/10.48550/arxiv.1803.06443openalex-snapshot
Communication Compression for Decentralized Training
inferredcites →https://doi.org/10.48550/arxiv.1806.01259openalex-snapshot
Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation
inferredcites →https://doi.org/10.48550/arxiv.1806.07569openalex-snapshot
A Distributed Second-Order Algorithm You Can Trust
inferredcites →https://doi.org/10.48550/arxiv.1808.07576openalex-snapshot
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
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Communication-Efficient Distributed Strongly Convex Stochastic Optimization: Non-Asymptotic Rates
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Acoustic Detection of Lining Void: Realization with Light-Weight Algorithms and Edge Devices
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Branchy-GNN: A Device-Edge Co-Inference Framework for Efficient Point Cloud Processing
inferred← citeshttps://doi.org/10.1109/icasspw62465.2024.10627110openalex-snapshot
Convergence Analysis of Semi-Federated Learning with Non-IID Data
inferred← citeshttps://doi.org/10.1109/icc42927.2021.9500298openalex-snapshot
Saddle Point Approximation Based Delay Analysis for Wireless Federated Learning
inferred← citeshttps://doi.org/10.1109/icc42927.2021.9500875openalex-snapshot
Fast Convergence Algorithm for Analog Federated Learning
inferred← citeshttps://doi.org/10.1109/icc42927.2021.9500918openalex-snapshot
UAV-Assisted Over-the-Air Computation
inferred← citeshttps://doi.org/10.1109/icc45041.2023.10278723openalex-snapshot
An Attack-Resistant Federated Edge Learning Framework for Integrated Sensing, Computing and Communications System
inferred← citeshttps://doi.org/10.1109/icc45041.2023.10279510openalex-snapshot
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9838381openalex-snapshot
Eliminating Communication Bottlenecks in Cross-Device Federated Learning with In-Network Processing at the Edge
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9839128openalex-snapshot
Temporal Connectivity as a Robustness Measure in NOMA Wireless Networks
inferred← citeshttps://doi.org/10.1109/icc52391.2025.11160772openalex-snapshot
Remote Training in Task-Oriented Communication: Supervised or Self-Supervised with Fine-Tuning?
inferred← citeshttps://doi.org/10.1109/iccc52777.2021.9580361openalex-snapshot
A Greedy Control Policy for Latency and Energy Constrained Wireless Federated Learning
inferred← citeshttps://doi.org/10.1109/iccc62479.2024.10681936openalex-snapshot
Communication-efficient Federated Learning with Privacy Enhancing via Probabilistic Scheduling
inferred← citeshttps://doi.org/10.1109/icccworkshops62562.2024.10693756openalex-snapshot
Multi-Device Cooperative Fine-Tuning of Foundation Models at the Network Edge
inferred← citeshttps://doi.org/10.1109/icceic60201.2023.10426713openalex-snapshot
Energy Efficient Federated Learning Joint Communication and Computation Framework Over Wireless Networks
inferred← citeshttps://doi.org/10.1109/iccsm57214.2022.00011openalex-snapshot
Towards MLOps in Mobile Development with a Plug-in Architecture for Data Analytics
inferred← citeshttps://doi.org/10.1109/iccworkshops49005.2020.9145209openalex-snapshot
Parallel Deep Reinforcement Learning Based Online User Association Optimization in Heterogeneous Networks
inferred← citeshttps://doi.org/10.1109/iccworkshops50388.2021.9473527openalex-snapshot
Over-the-Air Computation via Cloud Radio Access Networks
inferred← citeshttps://doi.org/10.1109/iccworkshops50388.2021.9473694openalex-snapshot
Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation
inferred← citeshttps://doi.org/10.1109/iccworkshops50388.2021.9473728openalex-snapshot
Reconfigurable Intelligent Surface Assisted Federated Learning with Privacy Guarantee
inferred← citeshttps://doi.org/10.1109/iccworkshops53468.2022.9814684openalex-snapshot
Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
inferred← citeshttps://doi.org/10.1109/iccworkshops57953.2023.10283612openalex-snapshot
STAR-RIS Assisted Over-the-Air Vertical Federated Learning in Multi-Cell Wireless Networks
inferred← citeshttps://doi.org/10.1109/iccworkshops67674.2025.11162413openalex-snapshot
Dynamic Weight Fusion with Entropy Optimization for Enhanced Distributed Object Detection and Resource Allocation
inferred← citeshttps://doi.org/10.1109/icdcs57875.2023.00066openalex-snapshot
SocialEdge: Socialized Learning-Based Request Scheduling for Edge-Cloud Systems
inferred← citeshttps://doi.org/10.1109/iceccme64568.2025.11277833openalex-snapshot
C-V2X Based Vehicle Movement Prediction for Connected Vehicle Application
inferred← citeshttps://doi.org/10.1109/icecet58911.2023.10389601openalex-snapshot
Leveraging the Decentralised Open IoT Security Protocol ((d)OISP)™: Facilitating Edge-Based Artificial Intelligence in Large-Scale Network Infrastructures
inferred← citeshttps://doi.org/10.1109/icict57646.2023.10134420openalex-snapshot
Performance Improvement Strategies of Edge-Enabled Social Impact Applications
inferred← citeshttps://doi.org/10.1109/icnc59896.2024.10556364openalex-snapshot
Straggler Mitigation in Edge Computing with Coded Compressed Sensing
inferred← citeshttps://doi.org/10.1109/icoin63865.2025.10993081openalex-snapshot
Optimized Cooperative Inference for Energy-Efficient and Low-Latency Mobile Edge Computing
inferred← citeshttps://doi.org/10.1109/icpads67057.2025.11322874openalex-snapshot
FedTeddi: Temporal Drift and Divergence Aware Scheduling for Timely Federated Edge Learning
inferred← citeshttps://doi.org/10.1109/icsintesa68165.2025.11413720openalex-snapshot
Edge-AI for Adversarial IoT: A Resilient Framework for Mission-Critical Intelligence
inferred← citeshttps://doi.org/10.1109/icsp58490.2023.10248783openalex-snapshot
Cluster Head Selection and Cluster Construction for Federated Learning in Mobile Ad Hoc Networks
inferred← citeshttps://doi.org/10.1109/ictc66702.2025.11389001openalex-snapshot
Quantum-Enhanced Edge Intelligence: Bridging Quantum Computing and Distributed AI
inferred← citeshttps://doi.org/10.1109/ietacs68750.2025.11385357openalex-snapshot
Edge-Optimized Agentic AI for Stochastic Communication Modeling in Digital Systems
inferred← citeshttps://doi.org/10.1109/ietacs68750.2025.11385778openalex-snapshot
AI Augmented IoT Framework for Precision Coal Wagon Loading Using STM32 and Cloud Based Weight Control
inferred← citeshttps://doi.org/10.1109/iicspi66775.2025.11438055openalex-snapshot
Utility-Driven Collaborative Edge and Cloud Intelligence Framework for IoT Systems
inferred← citeshttps://doi.org/10.1109/infocom59046.2026.11571696openalex-snapshot
Understanding Network Impact of Generative AI: Application-Level Traffic Measurement
inferred← citeshttps://doi.org/10.1109/ipccc51483.2021.9679419openalex-snapshot
Communication-Efficient Quantized SGD for Learning Polynomial Neural Network
inferred← citeshttps://doi.org/10.1109/iri69576.2026.00057openalex-snapshot
On Optimal Modality Compression for Bandwidth Constrained Multimodal Fusion
inferred← citeshttps://doi.org/10.1109/iscc65549.2025.11326072openalex-snapshot
Robust Multimodal Information Bottleneck for Satellite-to-Ground Task-Oriented Communication
inferred← citeshttps://doi.org/10.1109/isit45174.2021.9517780openalex-snapshot
Over-the-Air Decentralized Federated Learning
inferred← citeshttps://doi.org/10.1109/isit54713.2023.10206661openalex-snapshot
Fundamental Limits of Distributed Linearly Separable Computation under Cyclic Assignment
inferred← citeshttps://doi.org/10.1109/isit57864.2024.10619217openalex-snapshot
Computation Selection: Scheduling Users to Enable Over-the-Air Federated Learning
inferred← citeshttps://doi.org/10.1109/isvlsi65124.2025.11130213openalex-snapshot
Optimization and Security of AI Models for Deployment at Edge: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/itw55543.2023.10161632openalex-snapshot
Coded Distributed Computing for Hierarchical Multi-task Learning
inferred← citeshttps://doi.org/10.1109/jiot.2020.2979523openalex-snapshot
Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
inferred← citeshttps://doi.org/10.1109/jiot.2021.3130444openalex-snapshot
Federated Learning in Multi-RIS-Aided Systems
inferred← citeshttps://doi.org/10.1109/jiot.2022.3168066openalex-snapshot
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
inferred← citeshttps://doi.org/10.1109/jiot.2022.3176400openalex-snapshot
A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges
inferred← citeshttps://doi.org/10.1109/jiot.2022.3188544openalex-snapshot
STAR-RIS Integrated Nonorthogonal Multiple Access and Over-the-Air Federated Learning: Framework, Analysis, and Optimization
inferred← citeshttps://doi.org/10.1109/jiot.2022.3201117openalex-snapshot
Trustworthy Federated Learning via Blockchain
inferred← citeshttps://doi.org/10.1109/jiot.2023.3262620openalex-snapshot
Clustered Scheduling and Communication Pipelining for Efficient Resource Management of Wireless Federated Learning
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