隐私计算与数据要素 · 全部实体（第 81 / 100 页）

本页收录第 8001–8100 条，共 10000 条 · 返回 隐私计算与数据要素 首页

• Enhancing Privacy-Preserving of Heterogeneous Federated Learning Algorithms Using Data-Free Knowledge Distillation
  preprints 2024 置信度 0.74
• Privacy-Enhanced Sentiment Analysis in Mental Health: Federated Learning with Data Obfuscation and BERT
  preprints 2024 置信度 0.74
• DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank Adaptation
  preprints 2024 置信度 0.74
• A systematic survey on the application of federated learning in mental state detection and human activity recognition
  preprints 2024 置信度 0.74
• IOT edge computing layer modification based cyber-attack detection using Federated-Active Learning
  Abstract The Internet of Things and its practical uses are becoming more widespread as the number of connected devices increases, but it always carries a risk to network security. Therefore, it is vital for an IoT network design to rapidly and accurately ident…
  preprints J Vinothini, Srie Vidhya Janani E 2024 置信度 0.74
• Adaptive Clustering-Enabled Large-Scale Decentralized Federated Learning
  Since there exists a single point of server failure in conventional centralized federated learning, the decentralized federated learning (DFL) framework has become increasingly popular in recent years. However, when a large number of edge devices participate i…
  preprints Xuang Liang, Jianhua Tang, Marie Siew, Tony Q S Quek 2024 置信度 0.74
• Considerations on Novel Network Edge Physical Nodes Architectures Leveraging A Bottom-Up Technology-Centric Approach Empowered by Micro/Nanotechnologies (MEMS/NEMS) and Federated Learning
  preprints 2024 置信度 0.74
• FedWell: A Federated Framework for Privacy-Preserving Occupant Stress Monitoring in Smart Buildings
  preprints 2024 置信度 0.74
• A Practical Implementation to Federated Learning: Detecting Backdoor Attack on Next- word Prediction Model
  preprints 2024 置信度 0.74
• FMPA: Fragment Model Poisoning Attack in Federated Learning
  Abstract Federated learning is a distributed machine learning method that enables multiple participants to jointly train a machine learning model while preserving data privacy. However, its distributed nature makes federated learning vulnerable to Byzantine at…
  preprints Zhiqiang Ren, Xuebin Chen, Changsheng Qu 2024 置信度 0.74
• A Privacy-Preserving Data Augmentation Approach for Credit Card Fraud Detection
  europepmc 2024 置信度 0.80
• Quantum-Inspired Federated Learning for Privacy-Preserving and Communication- Efficient Healthcare IoT Systems
  Abstract With the increasing deployment of healthcare IoT (HIoT) systems, it is crucial to solve the data privacy problem and avoid information leakage while ensuring communications efficiency. Traditional FL models are usually decentralized, but they often fa…
  preprints Subaranjani T, Stephan Antony Raj A 2024 置信度 0.74
• Federated Learning Framework for Intrusion Detection System in Internet of Vehicles with Memory-Augmented Deep Autoencoder
  preprints 2024 置信度 0.74
• A Daily Load Forecasting Method Based on Federated Learning and Transformer Model
  preprints 2024 置信度 0.74
• Data Science and Machine Learning for Network Management in Telecommunication Systems: Trends and Opportunities
  preprints 2024 置信度 0.74
• Federated Learning-based Content Caching Strategy for Edge Computing
  Abstract In the realm of edge computing, effective content caching stands as a pivotal strategy to manage the exponential surge of mobile data within 5G networks. Content caching revolves around enabling the local storage of content in caches, ensuring swift a…
  preprints V Nivethitha, G Aghila 2024 置信度 0.74
• FedPyDESeq2: a federated framework for bulk RNA-seq differential expression analysis
  preprints 2024 置信度 0.74
• Federated Learning in Dynamic and Heterogeneous Environments: Advantages, Performances, and Privacy Problems
  preprints 2024 置信度 0.74
• Feasibility of training federated deep learning oropharyngeal primary tumor segmentation models without sharing gradient information
  preprints 2024 置信度 0.74
• A Bijection-backdoor-based Adversarial Examples Defense Method in Federated Learning
  preprints 2024 置信度 0.74
• FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings
  preprints 2024 置信度 0.74
• Personalized Federated Learning with Adaptive Information Fusion
  Abstract Data heterogeneity is a key challenge in the field of federated learning. Many existing personalized federated learning approaches focus on the performance of local models, neglecting the generalization capabilities of the global model, which may not …
  preprints Liming Chai, Wenjun Yu, Nanrun Zhou 2024 置信度 0.74
• A robust federated biased learning algorithm for time series forecasting 
  Abstract The federated averaging algorithm (FedAvg) is extensively used for multi-sensor data modeling but often overlooks the unique characteristics of local models when privacy and data security are not considered. This study introduces a novel federated lea…
  preprints Mingli Song, Xinyu Zhao, Witold Pedrycz 2024 置信度 0.74
• Privacy-Preserving Federated Transfer Learning for Multi-Class Few-Shot Classification
  preprints 2024 置信度 0.74
• PerFedHypID: A Personalized Federated Hypernetworks based aggregation approach for Intrusion Detection Systems
  europepmc 2024 置信度 0.80
• Merging Subgroup Information to Supplement Personal Information for Personal Federated Learning via Model Clustering
  Abstract Personalized federated learning represents a pivotal strategy for addressing the challenges posed by statistical heterogeneity in federated learning. Clients optimize their models by leveraging information from other clients through a global model. De…
  preprints Xuan Cai, Wenan Zhou 2024 置信度 0.74
• Federated Learning for Optimized Resource Allocation in Power Line Communication Systems
  This paper introduces a novel resource allocation algorithm, Priority-Aware Federated Resource Allocation (PAFRA), tailored for Power Line Communication (PLC) systems. Utilizing a federated learning framework, PAFRA optimizes the distribution of limited spectr…
  preprints Ruowen Yan, QIAO LI, Huagang Xiong 2024 置信度 0.74
• Privacy-Preserving Federated Learning-Based Intrusion Detection Technique for Cyber-Physical System
  preprints 2024 置信度 0.74
• Enhanced Algorithmic Convergence Analysis for Federated Low-Rank Matrix Completion
  preprints 2024 置信度 0.74
• Federated Task-Adaptive Learning for Personalized Selection of Human IVF-derived Embryos
  preprints 2024 置信度 0.74
• The Contribution of Federated Learning to AI Development
  With the widespread application of artificial intelligence technology in various industries, users' attention to privacy and data security has increased significantly. Federated learning, as a new technology paradigm combining privacy-enhanced computing and ar…
  preprints 2024 置信度 0.74
• Blockchain-based distributed federated learning using proof of accuracy consensus
  Abstract This paper explores integrating federated learning (FL) and blockchain tech- nology, two burgeoning fields in information technology. Despite their growing popularity, both domains face significant challenges. In federated learning, the primary concer…
  preprints Aghil Sadegh, Amir Jalaly Bidgoly 2024 置信度 0.74
• Blockchain Based Federated Learning Models Methods and Applications
  This paper systematically discusses the application and development of federated learning in data privacy protection and data value sharing. With the rapid development of global information technology, especially the explosive growth of data from Internet of T…
  preprints Rahul Sharma, Kritika Sharma, Priya Patel 2024 置信度 0.74
• BPPFL: A Blockchain-Based Framework for Privacy-Preserving Federated Learning
  Abstract Federated Learning (FL) offers a collaborative approach to training machine learning models while preserving data privacy. However, FL faces significant privacy and security challenges, such as identity disclosure and model inference attacks. To this …
  preprints Muhammad Asad, Safa Otoum 2024 置信度 0.74
• Trust management for IoT devices based on federated learning and blockchain
  Abstract The rapid growth of IoT devices and the increasing demand for device interaction between different network partitions have significantly pressured IoT device management. To realize cross-domain trust integration between different partitioned devices, …
  preprints Liang Wang, Yilin Li, Lina Zuo 2024 置信度 0.74
• A Realistic Greedy Parameter Aggregation Approach for Federated Learning Packet Transmissions
  Abstract Federated Learning (FL) enables decentralized machine learning while preserving data privacy. Despite extensive research on FL frameworks and simulations, packet skewness due to poor network conditions remains understudied. This paper proposes a greed…
  preprints Bright K Mahembe, Clement N Nyirenda, Omowunmi Isafiade 2024 置信度 0.74
• Federated Multiple Imputation for Variables that Are Missing Not At Random in Distributed Electronic Health Records
  preprints 2024 置信度 0.74
• Incremental YOLOv5 for Federated Learning in Cotton Pest and Disease Detection with Blockchain Sharding
  preprints 2024 置信度 0.74
• Federated Gradient Boosting using Minimal Variance Sampling
  preprints 2024 置信度 0.74
• Improving Multimodal Reasoning in Large Language Models via Federated Example Selection
  preprints 2024 置信度 0.74
• From Theory to Practice: Real-World Implementation of Artificial Intelligence and Machine Learning in Pharmacy Settings
  preprints 2024 置信度 0.74
• treeXnets: Comparing Federated Tree-BasedModels and Neural Networks on Tabular Data
  preprints 2024 置信度 0.74
• Privacy and Security Challenges in Federated Learning for UAV Systems: A Comprehensive Review
  Unmanned Aerial Vehicles (UAVs) have become indispensable assets in various sectors, leveraging their mobility and data collection capabilities. However, privacy and security concerns have fueled interest in Federated Learning (FL) as a solution. FL, decentral…
  preprints Ahmed Al Farsi, Ajmal Khan, Muhammad Rizwan, Mohammed M. Bait-Suwailam 2024 置信度 0.74
• Dynamic Network Slicing Orchestration in Open 5G Networks using Multi-Criteria Decision Making and Secure Federated Learning Techniques
  Abstract Network slicing enables new revenue opportunities for service providers by allowing them to offer customized network services tailored to various industry verticals and use cases. 5G network uses slicing technology to enable the creation of tailored n…
  preprints Hisham A. Kholidy 2024 置信度 0.74
• Federated Learning Incentivize with Privacy-Preserving for IoT in Edge Computing in the Context of B5G
  Abstract Federated learning and edge computing have resulted in the broad adoption of internet of Things (IoT) due to their fast reaction times and low connection costs. In general, edge computing requires users to send raw data to a central server for further…
  preprints Nasir Ahmad Jalali, Hongsong Chen 2024 置信度 0.74
• Evaluating Reproducibility in Psychology: A Machine Learning-Based Large-Scale Study on Predicting Replication Success
  preprints 2024 置信度 0.74
• A Privacy Preserving Federated Learning BasedIoT Framework Using Cloud Computing
  Abstract This abstract explores the transformative impact of IoT on modern life, empha- sizing the integration of Federated Learning (FL), Edge Computing, and Secure Offloading in AI applications. The rapid evolution of IoT has revolutionized com- mercial oper…
  preprints Wasim Ahmad, Muhammad Amin Almaiah, Bakht Sher Ali, Aitizaz Ali 2024 置信度 0.74
• ZDKD-FLID:Zero-Data Knowledge Distillation of Federated Learning for Intrusion Detection
  Abstract Over the years, federated learning-based intrusion detection has attracted attention because it preserves data privacy and improves the detection capabilities of local models. However, the majority of existing methods in this domain are tailored for h…
  preprints TiaoKang Gao, XiaoNing Jin, Yingxu Lai 2024 置信度 0.74
• Explainable, federated deep learning model predicts disease progression risk of cutaneous squamous cell carcinoma
  preprints 2024 置信度 0.74
• FedAEF: Optimizing federated learning with mining and enhancing local data features
  preprints 2024 置信度 0.74
• FedCEA: Efficient Adaptive Personalized Federated Learning based on Critical Learning Periods
  Abstract Federated learning (FL) faces significant challenges due to statistical heterogeneity, which undermines the global model's generalization capability across diverse clients. Personalized FL (pFL) has been extensively studied to address this, but most e…
  preprints Yichun Yu, Xiaoyi Yang, Zheping Chen, Yuqing Lan 等 2024 置信度 0.74
• Multi-Level Defense Strategy for Vertical Federated Learning Against Label Inference Attacks
  Abstract Vertical federated learning (VFL) is increasingly recognized as an indispensable paradigm. Especially in the medical field, where the protection of data privacy plays an indispensable role. In the healthcare domain, adherence to stringent regulatory f…
  preprints Linlong Wang, Chungen Xu, Pan Zhang, Yiting Liu 2024 置信度 0.74
• Accelerated Federated Learning Using Self-Adapting Bat Algorithm
  Abstract Federated learning (FL) is an advanced distributed machine learning (ML) framework designed to address issues related to data silos and data privacy. A significant challenge in FL is the non-independent and identically distributed (Non-IID) nature of …
  preprints Jie Wang, Chaochao Sun, Yuan Peng 2024 置信度 0.74
• Federated Learning-Based Ransomware Detection via Indicators of Compromise
  Abstract Ransomware attacks have become increasingly prevalent and sophisticated, posing significant threats to data security and organizational operations worldwide. Leveraging a federated learning-based approach, this research presents a novel and significan…
  preprints Shota Koike, Hanako Tanaka, Misaki Maeda 2024 置信度 0.74
• Federated deep learning enables cancer subtyping by proteomics
  preprints 2024 置信度 0.74
• Granular Neural Networks Learning for Time Series Prediction under a Federated Scenario
  Abstract Granular neural networks (GNNs) are a type of prediction models outputting information granules and GNNs not only provide more abstract results and a granular structure but also reveal a flexible nature that can be adjusted by users. As a promising to…
  preprints Mingli Song, Xinyu Zhao 2024 置信度 0.74
• A Fair Contribution Measurement Method for Federated Learning
  preprints 2024 置信度 0.74
• Peak-Controlled Logits Poisoning Attack in Federated Distillation
  preprints 2024 置信度 0.74
• Artificial Intelligence Transformations in Digital Advertising: Historical Progression, Emerging Trends, and Strategic Outlook
  preprints 2024 置信度 0.74
• A Load Forecasting Method of New Power System Based on Personalized Federated Learning
  Abstract The emerging distributed generation technology in new power systems encounters the challenges of unstable efficiency and high accuracy of prediction models. The generalization ability of prediction models is hindered by variations in users’ behavioral…
  preprints Yang Shen, Zewen Li, Fangming Deng, Bo Gao 2024 置信度 0.74
• A novel Federated Learning method with Domain Adaptation and Model Selection for Intrusion Detection
  preprints 2024 置信度 0.74
• Fast-CFLB: A Privacy-Preserving Data Sharing System for Internet of Vehicles Using Ternary Federated Learning and Blockchain
  preprints 2024 置信度 0.74
• Using the Nucleolus for Incentive Allocation in Vertical Federated Learning
  crossref Afsana Khan, Marijn ten Thij, Frank Thuijsman, Anna Wilbik 2025-01-21T18:22:35Z 置信度 0.70
• Comparative Evaluation of Clustered Federated Learning Method
  crossref Michael Ben Ali, Omar El-Rifai, Imen Megdiche, André Peninou 等 2025-01-21T18:22:35Z 置信度 0.70
• Energy-efficient federated learning algorithms
  crossref Amutha Prabakar Muniyandi, Daniel Arockiam, Feslin Anish Mon, N. Deepa 2025-01-20T05:27:31Z 置信度 0.70
• MC-PPHFL: Privacy-Preserving Hierarchical Federated Learning with a Secure Multi-Chain Aggregation
  crossref Safaá Fallatah, Floriana Grasso, Alexei Lisitsa 2025-01-21T18:22:35Z 置信度 0.70
• Federated sequential decision making: Bayesian optimization, reinforcement learning, and beyond
  crossref Zhongxiang Dai, Flint Xiaofeng Fan, Cheston Tan, Trong Nghia Hoang 等 2024-02-23T09:49:23Z 置信度 0.70
• Energy-efficient federated learning
  crossref Vijay Ramalingam, A. Arul Prakash, S. Vignesh, R. Rahin Batcha 等 2025-01-20T05:27:31Z 置信度 0.70
• Seamless Integration: Sampling Strategies in Federated Learning Systems
  crossref Tatjana Legler, Vinit Hegiste, Martin Ruskowski 2025-01-21T18:22:35Z 置信度 0.70
• Flotta: A Secure and Flexible Spark-Inspired Federated Learning Framework
  crossref Claudio Bonesana, Daniele Malpetti, Sandra Mitrović, Francesca Mangili 等 2025-01-21T18:22:35Z 置信度 0.70
• Efficient Hierarchical Federated Learning for Unlabeled Edge Devices
  crossref 2024-03-21T08:41:31Z 置信度 0.70
• A Review on Various Protocols in Federated Learning
  crossref H. T. Chethana, C. D. Divya, Tanuja Kayarga 2024-06-07T01:34:57Z 置信度 0.70
• Government and economic regulations on federated learning in emerging digital healthcare systems
  crossref Abdulwaheed Musa, Abdulhakeem Oladele Abdulfatai, Segun Ezekiel Jacob, Daniel Favour Oluyemi 2024-06-07T07:08:38Z 置信度 0.70
• Research Advanced in Federated Learning
  crossref Ruixin Gao 2024-09-19T12:37:25Z 置信度 0.70
• Resource Management for Federated Learning
  crossref Mingzhe Chen, Shuguang Cui 2024-02-19T05:04:40Z 置信度 0.70
• FedERA: Framework for Federated Learning with Diversified Edge Resource Allocation
  crossref Anupam Borthakur, Aditya Kasliwal, Asim Manna, Dipyan Dewan 等 2025-01-21T18:22:35Z 置信度 0.70
• Revolutionizing Healthcare through Federated Learning
  crossref Amrina Rahman, Md. Mushfiqur Rahman, Farhana Yasmin 2024-07-29T04:04:57Z 置信度 0.70
• Discrepency-Aware Clustered Federated Learning
  crossref Peifeng Zhang, Chen Jiahui 2024-01-11T01:51:33Z 置信度 0.70
• Toward Green Federated Learning
  crossref Minsu Kim, Walid Saad 2024-09-03T07:02:43Z 置信度 0.70
• Federated Optimization Algorithms
  crossref S. Biruntha, S. Rajalakshimi, M. Kavitha 2024-07-18T08:39:48Z 置信度 0.70
• Fedimp: The  Federated Impurity Weighting Algorithm for Improving Convergence in Federated Learning
  crossref Hai Anh Tran, Cuong Ta, Truong Tran 2024-09-04T21:19:09Z 置信度 0.70
• Federated Learning Shaping the Future of Smart City Infrastructure
  crossref Raj Kishor Verma, Kaushal Kishor, Antonino Galletta 2024-09-20T17:25:42Z 置信度 0.70
• Federated Learning for Mobile Edge Computing
  crossref Mingzhe Chen, Shuguang Cui 2024-02-19T05:04:40Z 置信度 0.70
• Fundamentals and Preliminaries of Federated Learning
  crossref Mingzhe Chen, Shuguang Cui 2024-02-19T05:04:40Z 置信度 0.70
• Federated Learning for Autonomous Vehicles Control
  crossref Mingzhe Chen, Shuguang Cui 2024-02-19T05:04:40Z 置信度 0.70
• The Future of Large Language Models (and AI) is Federated
  crossref Nicholas Lane 2025-01-21T18:22:35Z 置信度 0.70
• Federated Multi-Task Learning to Solve Various Healthcare Challenges
  crossref Seema Pahwa, Amandeep Kaur 2024-07-29T08:04:57Z 置信度 0.70
• Federated Learning-Based Smart Transportation Solutions
  crossref Sivabalan Settu, Raveendra Reddy, Appalaraju Muralidhar, Thangavel Murugan 等 2024-11-29T17:15:57Z 置信度 0.70
• Blockchain-based federated learning in internet of health things
  crossref B. Akoramurthy, B. Surendiran, K. Dhivya, Subrata Chowdhury 等 2024-06-07T07:09:02Z 置信度 0.70
• Securing Federated Deep Learning
  crossref Atharva Saraf, Shaurya Sameer Talewar, Susanta Das, Khushbu Trivedi 等 2024-11-29T17:15:57Z 置信度 0.70
• Healthcare Informatics Security Issues and Solutions Using Federated Learning
  crossref Sachin A. Goswami, Saurabh Dave, Kashyap C. Patel 2024-09-20T17:25:42Z 置信度 0.70
• Federated Learning for Securing Data Access and its Applications in Healthcare
  crossref Atharva Sajanikar, Deepthi Gupta, H. L. Gururaj 2024-06-07T01:34:57Z 置信度 0.70
• Incremental Data Aware Vertical Federated Learning
  crossref Yuzhi Liang, Yixiang Chen 2024-11-12T21:37:13Z 置信度 0.70
• Fundamental Theory of Federated Learning, Protocols and Enabling Technologies for Healthcare
  crossref Abdullah Abdul Sattar Shaikh, M. S. Bhargavi 2024-06-07T01:34:57Z 置信度 0.70
• CrowdGuard: Federated Backdoor Detection in Federated Learning
  crossref Phillip Rieger, Torsten Krauß, Markus Miettinen, Alexandra Dmitrienko 等 2024-02-10T16:35:08Z 置信度 0.70
• Fairness in federated learning
  crossref Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, Rachael Hwee Ling Sim 等 2024-02-23T09:48:57Z 置信度 0.70
• Federated Learning Techniques and Its Application in the Healthcare Industry
  crossref D. U. Latha, D. N. Varshitha, C. Shankara 2024-06-07T01:34:57Z 置信度 0.70
• Advancements and Applications of Federated Learning in Biometric Recognition
  crossref Zhengliang Lyu 2026-02-19T17:36:42Z 置信度 0.70
• Enhancing Privacy and Efficiency in IoT through Federated Learning
  crossref Nazeer Shaik 2024-07-12T10:39:38Z 置信度 0.70
• An overview of federated learning: empowering decentralized intelligence
  crossref Ghanshyam Prasad Dubey, Ayush Giri, Daniel Arockiam, V. Sathya Priya 2025-01-20T05:27:31Z 置信度 0.70