{"total":71,"rows":[{"id":"2111.08211","title":"FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning","created":"2021-11-16","cited_by_count":39,"area":null},{"id":"2308.08896","title":"Optimal Resource Allocation for U-Shaped Parallel Split Learning","created":"2023-08-17","cited_by_count":33,"area":null},{"id":"2108.03980","title":"Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness","created":"2021-07-30","cited_by_count":15,"area":null},{"id":"2203.05222","title":"Similarity-based Label Inference Attack against Training and Inference of Split Learning","created":"2022-03-10","cited_by_count":15,"area":null},{"id":"2208.13141","title":"Federated Learning of Large Models at the Edge via Principal Sub-Model Training","created":"2022-08-28","cited_by_count":13,"area":null},{"id":"2305.04146","title":"Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information","created":"2023-05-06","cited_by_count":13,"area":null},{"id":"2312.14227","title":"ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection","created":"2023-12-21","cited_by_count":12,"area":null},{"id":"2101.11896","title":"Self-supervised Cross-silo Federated Neural Architecture Search","created":"2021-01-28","cited_by_count":11,"area":null},{"id":"2109.09246","title":"Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance","created":"2021-09-19","cited_by_count":11,"area":null},{"id":"2212.06378","title":"Robust Split Federated Learning for U-shaped Medical Image Networks","created":"2022-12-13","cited_by_count":11,"area":null},{"id":"2310.10483","title":"Passive Inference Attacks on Split Learning via Adversarial Regularization","created":"2023-10-16","cited_by_count":9,"area":null},{"id":"2101.04800","title":"Personalized Federated Deep Learning for Pain Estimation From Face Images","created":"2021-01-12","cited_by_count":8,"area":null},{"id":"2112.01637","title":"AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning","created":"2021-12-02","cited_by_count":8,"area":null},{"id":"2104.07158","title":"Federated Learning-based Active Authentication on Mobile Devices","created":"2021-04-14","cited_by_count":7,"area":null},{"id":"2107.09546","title":"Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions","created":"2021-07-20","cited_by_count":7,"area":null},{"id":"2306.14638","title":"FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling","created":"2023-06-26","cited_by_count":7,"area":null},{"id":"2405.02081","title":"A Mutual Information Perspective on Federated Contrastive Learning","created":"2024-05-03","cited_by_count":7,"area":null},{"id":"2501.06650","title":"SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)","created":"2025-01-11","cited_by_count":7,"area":null},{"id":"2510.21155","title":"Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach","created":"2025-10-24","cited_by_count":7,"area":null},{"id":"2308.15783","title":"Split Without a Leak: Reducing Privacy Leakage in Split Learning","created":"2023-08-30","cited_by_count":6,"area":null},{"id":"2409.08538","title":"An Efficient Privacy-aware Split Learning Framework for Satellite Communications","created":"2024-09-13","cited_by_count":6,"area":null},{"id":"2410.19375","title":"COMSPLIT: A Communication-Aware Split Learning Design for Heterogeneous IoT Platforms","created":"2024-10-25","cited_by_count":5,"area":null},{"id":"2206.03852","title":"FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning","created":"2022-06-07","cited_by_count":4,"area":null},{"id":"2208.10553","title":"Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation","created":"2022-08-22","cited_by_count":4,"area":null},{"id":"2302.08618","title":"SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection","created":"2023-02-16","cited_by_count":4,"area":null},{"id":"2304.14976","title":"Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations","created":"2023-04-28","cited_by_count":4,"area":null},{"id":"2209.10119","title":"Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information","created":"2022-09-21","cited_by_count":3,"area":null},{"id":"2211.10948","title":"FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative Training","created":"2022-11-20","cited_by_count":3,"area":null},{"id":"2303.10624","title":"PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients","created":"2023-03-19","cited_by_count":3,"area":null},{"id":"2304.01502","title":"SLPerf: a Unified Framework for Benchmarking Split Learning","created":"2023-04-04","cited_by_count":3,"area":null},{"id":"2404.19582","title":"URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning","created":"2024-04-30","cited_by_count":3,"area":null},{"id":"2405.18707","title":"Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing","created":"2024-05-29","cited_by_count":3,"area":null},{"id":"2407.15738","title":"Parallel Split Learning with Global Sampling","created":"2024-07-22","cited_by_count":3,"area":null},{"id":"2501.13890","title":"Federated Granger Causality Learning for Interdependent Clients with State Space Representation","created":"2025-01-23","cited_by_count":3,"area":null},{"id":"2507.15816","title":"Federated Split Learning with Improved Communication and Storage Efficiency","created":"2025-07-21","cited_by_count":3,"area":null},{"id":"2601.10940","title":"HOSL: Hybrid-Order Split Learning for Memory-Constrained Edge Training","created":"2026-01-16","cited_by_count":3,"area":null},{"id":"2103.14291","title":"Vulnerability Due to Training Order in Split Learning","created":"2021-03-26","cited_by_count":2,"area":null},{"id":"2301.11468","title":"Multi-limb Split Learning for Tumor Classification on Vertically Distributed Data","created":"2023-01-27","cited_by_count":2,"area":null},{"id":"2309.04875","title":"Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference","created":"2023-09-09","cited_by_count":2,"area":null},{"id":"2405.04043","title":"Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference","created":"2024-05-07","cited_by_count":2,"area":null},{"id":"2406.02027","title":"Inference Attacks: A Taxonomy, Survey, and Promising Directions","created":"2024-06-04","cited_by_count":2,"area":null},{"id":"2409.12328","title":"SplitVAEs: Decentralized scenario generation from siloed data for stochastic optimization problems","created":"2024-09-18","cited_by_count":2,"area":null},{"id":"2410.09125","title":"Training on Fake Labels: Mitigating Label Leakage in Split Learning via Secure Dimension Transformation","created":"2024-10-11","cited_by_count":2,"area":null},{"id":"2412.14272","title":"Split Learning in Computer Vision for Semantic Segmentation Delay Minimization","created":"2024-12-18","cited_by_count":2,"area":null},{"id":"2505.05872","title":"A Taxonomy of Attacks and Defenses in Split Learning","created":"2025-05-09","cited_by_count":2,"area":null},{"id":"2111.11856","title":"Spatio-Temporal Split Learning for Autonomous Aerial Surveillance using Urban Air Mobility (UAM) Networks","created":"2021-11-15","cited_by_count":1,"area":null},{"id":"2211.16703","title":"An Efficient Split Fine-tuning Framework for Edge and Cloud Collaborative Learning","created":"2022-11-30","cited_by_count":1,"area":null},{"id":"2302.13514","title":"Applications of Federated Learning in Manufacturing: Identifying the Challenges and Exploring the Future Directions with Industry 4.0 and 5.0 Visions","created":"2023-02-27","cited_by_count":1,"area":null},{"id":"2309.02787","title":"Dynamic Encoding and Decoding of Information for Split Learning in Mobile-Edge Computing: Leveraging Information Bottleneck Theory","created":"2023-09-06","cited_by_count":1,"area":null},{"id":"2401.10859","title":"Ensembler: Protect Collaborative Inference Privacy from Model Inversion Attack via Selective Ensemble","created":"2024-01-19","cited_by_count":1,"area":null},{"id":"2404.17990","title":"TabVFL: Improving Latent Representation in Vertical Federated Learning","created":"2024-04-27","cited_by_count":1,"area":null},{"id":"2502.01289","title":"A Framework for Double-Blind Federated Adaptation of Foundation Models","created":"2025-02-03","cited_by_count":1,"area":null},{"id":"2508.08339","title":"SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning","created":"2025-08-11","cited_by_count":1,"area":null},{"id":"2510.13320","title":"RockNet: Distributed Learning on Ultra-Low-Power Devices","created":"2025-10-15","cited_by_count":1,"area":null},{"id":"2603.04437","title":"ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning","created":"2026-02-19","cited_by_count":1,"area":null},{"id":"2110.01474","title":"Distributed Learning Approaches for Automated Chest X-Ray Diagnosis","created":"2021-10-04","cited_by_count":0,"area":null},{"id":"2302.02245","title":"GAN-based Vertical Federated Learning for Label Protection in Binary Classification","created":"2023-02-04","cited_by_count":0,"area":null},{"id":"2305.01252","title":"HTPS: Heterogeneous Transferring Prediction System for Healthcare Datasets","created":"2023-05-02","cited_by_count":0,"area":null},{"id":"2310.18479","title":"Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments","created":"2023-10-27","cited_by_count":0,"area":null},{"id":"2311.05827","title":"AccEPT: An Acceleration Scheme for Speeding Up Edge Pipeline-parallel Training","created":"2023-11-10","cited_by_count":0,"area":null},{"id":"2401.03233","title":"Convergence Rate Maximization for Split Learning-based Control of EMG Prosthetic Devices","created":"2024-01-06","cited_by_count":0,"area":null},{"id":"2408.04310","title":"Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit","created":"2024-08-08","cited_by_count":0,"area":null},{"id":"2409.15558","title":"Stalactite: Toolbox for Fast Prototyping of Vertical Federated Learning Systems","created":"2024-09-23","cited_by_count":0,"area":null},{"id":"2410.24181","title":"Federated Black-Box Adaptation for Semantic Segmentation","created":"2024-10-31","cited_by_count":0,"area":null},{"id":"2504.06410","title":"PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks","created":"2025-04-08","cited_by_count":0,"area":null},{"id":"2507.07637","title":"HLF-FSL. A Decentralized Federated Split Learning Solution for IoT on Hyperledger Fabric","created":"2025-07-10","cited_by_count":0,"area":null},{"id":"2510.12494","title":"PubSub-VFL: Towards Efficient Two-Party Split Learning in Heterogeneous Environments via Publisher/Subscriber Architecture","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2601.18948","title":"Smart Split-Federated Learning over Noisy Channels for Embryo Image Segmentation","created":"2026-01-26","cited_by_count":0,"area":null},{"id":"2602.21928","title":"Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2608.18767","title":"Gradient Mirage: Trainable yet Label-Unidentifiable Gradients in Large Language Model Split Learning","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2608.23382","title":"Spectrum-Aware Bounds on Invertibility for Privacy-Enhancing Instance Encoding","created":"2026-08-24","cited_by_count":0,"area":null}],"next_cursor":null}