隐私计算与数据要素 · 全部实体（第 70 / 100 页）

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• Federated Learning with Logit Calibrated Distillation
  crossref Haopeng Wang, Tong Liu, Yangguang Cui, Zhenzhe Zheng 2025-10-06T13:45:57Z 置信度 0.70
• Federated learning-based diagnosis of epilepsy disease in healthcare 6.0
  crossref Monalisha Pattnaik, Deepti Rani Pattanaik, Sudev Kumar Padhi, Ashirbad Mishra 等 2025-03-20T10:28:47Z 置信度 0.70
• Partitioned, Federated, and Active Learning
  crossref 2025-04-29T02:07:28Z 置信度 0.70
• Artificial Intelligence-Enabled Federated Learning Techniques in Healthcare Sector
  crossref Shivani Sharma, Radhika Gour 2025-08-08T17:48:41Z 置信度 0.70
• A Federated Learning Scheme based on Fully Homomorphic Encryption
  crossref Yuqi GUO, Lin LI 2025-12-31T02:35:30Z 置信度 0.70
• Federated Learning-Based Intrusion Detection System for IoT Networks in Resource-Constrained Environments
  The fast increase in Internet of Things (IoT) solutions has widened the attacker window and poses a pressing requirement to find intrusion detection solutions that will create solutions that are more balanced in regard to security, efficiency, and privacy. In …
  crossref Michel Nguyen 2025-11-25T01:29:50Z 置信度 0.70
• Enhancing Data Privacy in Federated Learning: A Cryptographic Perspective
  crossref Sophia Haoran Chen, Yaokai Liu 2025-07-21T18:08:23Z 置信度 0.70
• Roadfed: A Multimodal Federated Learning System for Improving Road Safety
  crossref Yachao Yuan, Xingyu Chen 2025-04-09T02:40:15Z 置信度 0.70
• Graph-based Federated Learning for Fault Detection in Power Distribution Systems
  This paper presents a comprehensive analysis of Federated Learning (FL) applications in power grid systems, with a particular focus on edge computing implementation. We explore both centralized and decentralized FL architectures, introducing a novel graph-base…
  crossref Dmitry Bandurin, Norayr Matevosyan 2025-03-24T18:03:12Z 置信度 0.70
• Splitting Smarter: Differential Privacy for Secure Healthcare Federated Learning
  Split Federated Learning (SplitFed) has emerged as a decentralized method of training ML models that enables multiple healthcare parties to collaboratively models without sharing their raw data. This method is, however, vulnerable against label inference attac…
  crossref Munirat Yetunde, Raj Shukla, Tapadhir Das 2025-07-31T04:00:31Z 置信度 0.70
• A Personalized Federated Learning Framework for IoT Intrusion Detection
  crossref Dawit Dejene Bikila, Jan Čapek 2025-10-21T20:23:03Z 置信度 0.70
• Revolutionizing Smart Transportation with Federated Learning: Applications, Challenges, and Future Directions
  crossref Rashmi Sharma, Shilpa Choudhary, Monali Gulhane, Ankita Tiwari 2025-09-26T06:04:39Z 置信度 0.70
• Federal Learning Approach for Smart Cities
  crossref Rahul Vadisetty 2025-10-03T21:19:49Z 置信度 0.70
• Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks
  crossref M. Saeid HaghighiFard, Sinem Coleri 2025-11-25T16:51:12Z 置信度 0.70
• Federated Learning for Neural Disorders in Healthcare 6.0
  crossref Kishor Kumar Reddy C, Anindya Nag 2025-03-20T10:28:47Z 置信度 0.70
• Decision letter for "IoT-Enabled Electric Load Prediction via Federated Label Distribution Learning"
  crossref 2025-11-18T21:06:43Z 置信度 0.70
• Digital Imprints and Mitigating Persistent Ai Biases Through Federated Learning
  crossref Marko Jocic, James Davis 2025-08-02T13:42:34Z 置信度 0.70
• Decision letter for "IoT-Enabled Electric Load Prediction via Federated Label Distribution Learning"
  crossref 2025-11-18T21:06:43Z 置信度 0.70
• Review for "Breaking Interprovincial Data Silos: How Federated Learning Can Unlock Canada’s Public Health Potential"
  crossref 2026-03-14T21:10:36Z 置信度 0.70
• Federated Meta-Learning Framework for Detecting Blackhole Attacks
  crossref Samtony D., K. Victor 2026-07-31T14:48:22Z 置信度 0.70
• Federated Learning with Feature Space Separation for Speaker Recognition
  crossref Ying Meng, Zhihua Fang, Liang He 2025-10-22T11:47:41Z 置信度 0.70
• Secure Visual Data Processing via Federated Learning
  crossref Pedro Santos, Tânia Carvalho, Filipe Magalhães, Luís Antunes 2025-02-25T06:22:45Z 置信度 0.70
• Leader-Follower Federated Learning Framework: Heterogeneous Federated Learning based on Asymmetric Distillation
  crossref Lina Ge, Haisong Zhu, Ming Jiang, Zhe Wang 2026-02-02T20:42:41Z 置信度 0.70
• A Review of Secure Gradient Compression Techniques for Federated Learning in the Internet of Medical Things
  crossref Timoteo Kelly, Ahmad Alhonainy, Praveen Rao 2025-04-26T02:21:20Z 置信度 0.70
• Predicting Alzheimer’s Disease: A Case Study Using Federated Learning Framework
  crossref Aman Sharma, Mohit Pal, Aditya Soni, Rajni Mohana 2025-09-26T05:51:59Z 置信度 0.70
• Federated machine learning and augmented reality (AR)/virtual reality (VR)-based framework for schizophrenia diagnosis and therapy
  crossref Vijayakumar Ponnusamy, Nandini Manickam, Emilija Kisic, Nemanja Zdravković 2025-03-20T10:28:47Z 置信度 0.70
• A Selective Homomorphic Encryption Approach for Faster Privacy-Preserving Federated Learning
  Federated learning is a machine learning method that supports training models on decentralized devices or servers, where each holds its local data, removing the need for data exchange. This approach is especially useful in healthcare, as it enables training on…
  crossref Abdulkadir Korkmaz, Praveen Rao 2025-03-05T15:35:27Z 置信度 0.70
• Federated Learning for Integrating Diverse Speech Biomarkers for Parkinson's Disease Classification
  crossref Ruchira Pratihar, Ravi Sankar 2025-04-25T17:38:19Z 置信度 0.70
• Securing Collaborative Model Training: Navigating Privacy Challenges in Federated Learning for Industrial IoT
  crossref C. V. Suresh Babu, G. Suruthi 2025-09-26T05:47:32Z 置信度 0.70
• A Federated Learning Approach for Privacy-Aware Data Sharing Across Telecom Clouds
  crossref Feng Jian 2025-08-16T12:01:30Z 置信度 0.70
• Dfdg: Adaptive Federated Learning for Dynamic Graph-Based Traffic Forecasting
  crossref Muhammad Usman, Yugyung Lee 2025-02-19T21:39:11Z 置信度 0.70
• Review for "Breaking Interprovincial Data Silos: How Federated Learning Can Unlock Canada’s Public Health Potential"
  crossref 2026-03-14T21:10:36Z 置信度 0.70
• Federated Learning for Enterprise Data Integration: Examining the Application of Federated Learning to Integrate AI Models Without Centralizing Enterprise Data
  Enterprise organizations face increasing pressure to leverage distributed data assets for artificial intelligence advancement while maintaining strict data governance requirements. Conventional machine studying frameworks require the centralization of facts, w…
  crossref Tejaswi Bharadwaj Katta 2025-12-30T08:32:08Z 置信度 0.70
• A Critical Learning Period-Aware Incentive Mechanism for Federated Learning
  crossref Thanh Linh Nguyen, Quoc-Viet Pham 2025-09-30T17:36:40Z 置信度 0.70
• Probabilistic Label Flipping Attack in Federated Learning
  crossref Anee Sharma, Ningrinla Marchang 2025-09-26T17:35:05Z 置信度 0.70
• Optimized Local Updates in Federated Learning via Reinforcement Learning
  crossref Ali Murad, Bo Hui, Wei-Shinn Ku 2025-11-14T18:46:15Z 置信度 0.70
• Security Analysis of Federated Learning in Healthcare
  crossref Jessie Chen 2026-05-26T19:40:24Z 置信度 0.70
• Decentralized Intelligence for Cardiac Health: A Federated Learning Approach to Privacy-Conscious Disease Prediction
  crossref 2025-09-13T08:35:49Z 置信度 0.70
• Privacy-Preserving AI in Telecom: A Taxonomy and Survey of Federated Learning Applications
  crossref Juned Kazi 2025-08-18T16:41:28Z 置信度 0.70
• Message from the Technical Program Chairs
  crossref 2026-01-20T20:38:34Z 置信度 0.70
• IoT Security Enhancements in Smart Healthcare Using Federated Learning
  crossref Surekha Lanka, Taipida Moodhitaporn 2025-03-28T02:32:33Z 置信度 0.70
• Federated Learning and Deep Learning: A New Frontier for Real-World Applications
  crossref Sridhar K. 2025-01-25T06:17:18Z 置信度 0.70
• Penerapan Federated Learning dalam Keamanan Data Pengguna pada Aplikasi Mobile
  In the digital era that is full of user data processing, security and privacy are crucial issues, especially in mobile applications. Federated Learning (FL) emerged as an innovative solution in maintaining data confidentiality because the model training proces…
  crossref Ranto Siswanto, Muawan Bisri 2025-05-18T13:01:11Z 置信度 0.70
• Optimizing Value of Learning in Task-Oriented Federated Meta-Learning Systems
  crossref Bibo Wu, Fang Fang, Xianbin Wang 2025-09-26T17:34:55Z 置信度 0.70
• Federated Survival Analysis With Differential-Privacy-Inspired Noise: Single Round Release of Kaplan-Meier Curves
  crossref Narasimha Raghavan Veeraragavan, Jan F. Nygård 2026-01-20T20:38:34Z 置信度 0.70
• LotusFA: a Federated Analytics System for Federated Learning of Watermarked Data
  crossref Tao Ling, Siping Shi, Dan Wang, Yifei Zhu 等 2025-09-12T17:28:22Z 置信度 0.70
• Robust Blockchain-Based Federated Learning
  crossref Aftab Akram, Clémentine Gritti, Mohd Halip, Nur Kamarudin 等 2025-02-25T06:22:45Z 置信度 0.70
• Federated Learning-Based Classification of Sugarcane Leaf Diseases Using Deep Learning
  crossref Panuphan Injan, Sanya Khruahong 2025-12-23T18:29:39Z 置信度 0.70
• Real-time stroke detection based on deep learning and federated learning
  crossref Abdussalam Elhanashi, Sergio Saponara 2025-03-21T22:21:38Z 置信度 0.70
• Federated AI Observability in Multi-Cloud Microservices: A Secure and Scalable Federated Learning Perspective
  As artificial intelligence (AI) becomes integral to microservices deployed across multi-cloud environments, ensuring secure and scalable observability is critical. Traditional centralized observability methods often fail to address the privacy, compliance, and…
  crossref Bhaskara Garnimitta 2025-08-06T15:30:37Z 置信度 0.70
• Federated Learning for the Maritime and Offshore Industries: Training Machine Learning Models Without Data Sharing
  In the fast-evolving field of machine learning, data privacy and security are critical concerns, especially in sensitive and heavily regulated sectors such as offshore energy and maritime operations. Traditional centralized machine learning approaches require …
  crossref Gaspard Ducamp, Peter Kim, Eivind Ruth 2025-04-16T10:18:02Z 置信度 0.70
• Federated Learning–Based Approach for Crop Recommendation and Market Stability in Agriculture
  crossref Saurabh Kumar, Tejasva Maurya, Mritunjay Rai, Abhishek Saxena 2025-12-15T10:17:52Z 置信度 0.70
• pFedMMD:Personalized Federated Learning via Meta-Learning and Model Disentanglement
  crossref Jiang Hou 2025-09-25T17:52:17Z 置信度 0.70
• FedSent: Federated Learning-Based Privacy-Preserving English Sentiment Analysis
  crossref Zixiang Zhao, Jie Kong 2026-01-20T20:38:44Z 置信度 0.70
• Federated Learning-based Vehicle Edge Caching Optimization Strategy
  crossref Yali Wang, Shouhao Li 2025-09-17T17:29:48Z 置信度 0.70
• Multi-Agent Battlefield Game with Federated Reinforcement Learning
  crossref Fardeen Hasib Mozumder 2025-09-17T17:29:46Z 置信度 0.70
• Federated Learning for Energy Optimization in the Industrial Internet of Things: Applications and Challenges
  crossref Ankita Tiwari, Nitin Rakesh, Monali Gulhane 2025-09-26T05:44:34Z 置信度 0.70
• Federated Learning-Based Approach for Landslide Forecasting in Taiwan
  Landslides pose significant risks, often causing severe property damage and, in extreme cases, loss of life due to poorly timed evacuations. Accurate forecasting is, therefore, essential. Traditional landslide studies rely heavily on satellite imagery to analy…
  crossref Po-Wu Cheng, Wen-Ping Tsai 2025-03-14T19:28:01Z 置信度 0.70
• Personalized Federated Learning Based on Fine-grained Subgraphs
  crossref Jiawei Liu 2025-11-14T18:46:15Z 置信度 0.70
• Towards a Resilient Federated Edge Intelligence: A Testbed for Design, Analysis, and Validation of Federated Learning
  crossref Leo Janse van Rensburg, Liang Zhao 2025-08-15T18:11:58Z 置信度 0.70
• Federated Learning in Smart Farming: Applications and Challenges
  crossref Shashank Gupta, Shefali Arora, Shamimul Qamar 2025-08-08T17:48:57Z 置信度 0.70
• A Blockchain-Enabled Federated Adversarial Learning Framework for Robust Cyber Threat Intelligence Sharing
  crossref Deepika P 2025-06-20T16:59:36Z 置信度 0.70
• Fingerprinting Deep Learning Models via Network Traffic Patterns in Federated Learning
  crossref Md Nahid Hasan Shuvo, Moinul Hossain 2025-06-26T17:59:47Z 置信度 0.70
• Review for "FedDW: An Adaptive Weight Aggregation Federated Learning Framework for Multi-Institutional Collaborative Polyp Segmentation"
  crossref 2025-12-31T23:57:44Z 置信度 0.70
• Bridging Privacy and Personalization: How Federated Learning and Blockchain Are Transforming Smart Healthcare Devices
  Research shows that healthcare systems increasingly struggle with challenges due to demographic changes and rising chronic disease prevalence, driving necessary transitions from conventional reactive care delivered in facilities to proactive care models built …
  crossref Akram Gasmelseed 2025-11-06T04:21:39Z 置信度 0.70
• Leveraging Federated Learning for Multilingual and Private Language Models via Model Clustering
  crossref Gabriel U. Talasso, Allan M. de Souza, Luis F. G. Gonzalez, Eduardo Cerqueira 等 2026-01-20T20:38:34Z 置信度 0.70
• Enhancing Data Privacy in Cloud-Native Applications with Federated Learning
  Federated learning (FL), a cutting-edge approach to machine learning, allows models to be created across distributed devices while maintaining the privacy of sensitive data on the local nodes. This paradigm is pertinent to cloudnative apps since data security …
  crossref Harish Thummala, Avinash Reddy Kandlakunta 2025-02-03T08:49:22Z 置信度 0.70
• Pneumonia detection from X-ray images using federated learning–An unsupervised learning approach
  crossref Neeta Rana, Hitesh Marwaha 2024-12-03T18:09:38Z 置信度 0.70
• Learn Efficiently Without a Server: RIS-Aided Federated Learning
  crossref Anis Elgabli 2025-06-26T17:40:25Z 置信度 0.70
• Privacy-Preserving Rheumatism Detection Using Federated Learning
  crossref Bidita Sarkar Diba, Tasnim Jahin Mowla, Nazneen Nahar, Fahad Ahmed 等 2025-10-31T19:42:52Z 置信度 0.70
• Efficient Federated Model Aggregation through Neural Velocity
  crossref Gianluca Dalmasso, Pedro Porto Buarque de Gusmão, Attilio Fiandrotti, Marco Grangetto 2025-12-02T17:01:43Z 置信度 0.70
• Revolutionizing Industry 4.0: Multi-level Federated Learning for a Dynamic Ecosystem
  crossref Rashmi Sharma, Bharat Singh, Monali Gulhane, Piyush Chauhan 等 2025-09-26T05:44:19Z 置信度 0.70
• Privacy Protection for Medical Information in Federated Learning
  crossref Malyala Vaishnavi, Srikanth Vemuru, Afsana Khan 2025-08-08T17:48:16Z 置信度 0.70
• Enhancing Recommendation Systems with Federated Learning for Privacy-Preserving E-Commerce Platforms
  crossref Mohammad Reza Mahdiani 2025-02-08T22:39:38Z 置信度 0.70
• PrivacyShepherd: Federated Learning for SNP-Based Sheep Breed Identification
  This study presents an innovative federated learning framework that addresses the challenge of identifying the breeds of Iranian sheep using an SNP-based genotype dataset which contains the SNP values of four breeds of Iranian sheep. In the first phase of the …
  crossref Reza Nourmohammdi, Mohammad Hossein Moradi, Iman Behravan 2025-01-15T11:32:41Z 置信度 0.70
• Energy-Aware Adaptive Federated Learning for IoT Security in 6G
  Artificial intelligence (AI) and machine learning (ML) are widely adopted in sixth generation (6G) mobile networks. However, the deployment of AI in communication networks will require huge amounts of resources, such as computing, memory, bandwidth, and, as a …
  crossref Yasintha Rumesh, Pawani Porambage, Ijaz Ahmad 2025-10-27T20:39:36Z 置信度 0.70
• Fault-Tolerant Federated Learning Framework for Edge Devices in Unstable Networks
  Federated Learning (FL) has emerged as a critical paradigm for decentralized machine learning, enabling collaborative model training across edge devices, while preserving data privacy. However, the real-world deployment of edge devices faces challenges such as…
  crossref Praveen Kumar Myakala, Manan Agrawal 2025-05-01T13:41:27Z 置信度 0.70
• Review for "FedDW: An Adaptive Weight Aggregation Federated Learning Framework for Multi-Institutional Collaborative Polyp Segmentation"
  crossref 2025-12-31T23:57:44Z 置信度 0.70
• Federated Learning for Dynamic Route Optimization in SAP Transportation Management: Pioneering Sustainable Logistics
  In the face of rising environmental concerns and complex global logistics, SAP Transportation Management (TM) is pivotal for planning and executing efficient transportation operations. This research introduces a novel framework leveraging federated learning (F…
  crossref Srinivas Raju Gottimukkala 2025-08-26T20:19:58Z 置信度 0.70
• Federated Learning and Explainable AI for Personalized Healthcare in Resource-Limited Settings
  Abstract Artificial Intelligence (AI) has transformed healthcare, significantly advancing diagnostic tools, treatment methodologies, and personalized care systems. Despite these advancements, the adoption of AI in resource-constrained environments faces persis…
  crossref Milad Rahmati 2025-01-23T06:09:16Z 置信度 0.70
• PHiFL-TL: Personalized hierarchical federated learning using transfer learning
  crossref Afsaneh Afzali, Pirooz Shamsinejadbabaki 2024-12-09T02:56:22Z 置信度 0.70
• Learning from Tabular Data Silos without Data Sharing: A Contrastive Federated Learning Approach
  crossref Achmad Ginanjar, Xue Li, Priyanka Singh, Wen Hua 2025-11-24T22:39:59Z 置信度 0.70
• Private Aggregation for Byzantine-Resilient Heterogeneous Federated Learning
  crossref Maximilian Egger, Rawad Bitar 2025-11-21T18:39:40Z 置信度 0.70
• Federated Learning for Crop Yield Prediction
  crossref Gangadhara Doggalli, E. Santhoshini, R. Sujitha, G.R. Vishwas Gowda 等 2025-12-15T10:17:52Z 置信度 0.70
• Federated Learning for Low-Latency Emitter Identification from Space
  crossref Max Cui-Stein, Binoy Kurien 2025-07-14T17:40:12Z 置信度 0.70
• Adversarial Machine Learning for Enhanced Security and Byzantine Resilience in Federated Learning Architectures: A Comprehensive Review
  Federated Learning (FL) has rapidly emerged as a foundational paradigm shift in Artificial Intelligence (AI), specifically designed to address stringent privacy and data governance demands. Despite its inherent privacy-by-design architecture, FL is fundamental…
  crossref Maharshi S Patel, Gayatri S Pandi 2025-11-05T21:58:31Z 置信度 0.70
• Federated Edge Learning via Unmanned Aerial Vehicle
  crossref Yong Zhou, Wenzhi Fang, Yuanming Shi, Khaled B. Letaief 2025-08-29T12:52:19Z 置信度 0.70
• Optimization Study of FedDyn-Based Federated Learning Algorithm
  crossref Zihan Zhuo 2026-07-31T09:52:33Z 置信度 0.70
• Temporal Analysis of Adversarial Attacks in Federated Learning
  crossref Rohit Mapakshi, Sayma Akther, Mark Stamp 2025-05-09T03:21:59Z 置信度 0.70
• Harnessing the Power of Federated Learning for Agricultural Innovation
  crossref Abhishek, Mritunjay Rai, Anand Prakash Singh, Vishwanath Jha 2025-12-15T10:17:52Z 置信度 0.70
• Second-Order Algorithm for Federated Edge Learning
  crossref Yong Zhou, Wenzhi Fang, Yuanming Shi, Khaled B. Letaief 2025-08-29T12:52:26Z 置信度 0.70
• First-Order Algorithm for Federated Edge Learning
  crossref Yong Zhou, Wenzhi Fang, Yuanming Shi, Khaled B. Letaief 2025-08-29T12:52:28Z 置信度 0.70
• Optimizing neural disorder treatment through federated learning and multi-institutional data collaboration
  crossref T Monika Singh, C Kishor Kumar Reddy, Jagadeshwari Puttanapura, Srinath Doss 2025-03-20T10:28:47Z 置信度 0.70
• Robust Complex-Valued Federated Learning for Secure 6G Mobile Communications
  Federated learning (FL) has attracted interest as a decentralized machine learning paradigm, where multiple clients collaboratively train a shared model while retaining their raw data locally. By performing computations on-device and sending only model updates…
  crossref Anders Buvarp, Stefan Werner 2025-07-24T22:17:40Z 置信度 0.70
• Privacy-Preserving Intrusion Detection Systems in VANETs Using Federated Deep Learning
  crossref Garba M. 2025-07-07T15:17:20Z 置信度 0.70
• Enhanced Privacy Preserving Deep Learning Using Blockchain and Federated Learning
  crossref S. Usharani, P. Manju Bala, A. Balachandar, G. Glorindal 2025-11-07T13:28:15Z 置信度 0.70
• PRODIGY: Proximity- and Dissimilarity-Based Byzantine-Robust Federated Learning
  crossref Sena Ergisi, Luis Maßny, Rawad Bitar 2026-01-20T20:38:34Z 置信度 0.70
• Federated Learning for Intelligent Smart Grid Systems
  The evolution of conventional power networks into smart grids has been driven by the integration of digital communication, advanced sensing technologies, and intelligent control mechanisms. Machine learning techniques are increasingly employed to analyze large…
  crossref 2025-12-18T05:39:04Z 置信度 0.70
• Efficient Model Propagation for Peer-to-Peer Federated Learning using Minimum Spanning Tree and Gossip Networks
  crossref Alka Luqman, Riya Mahesh, Anupam Chattopadhyay 2025-07-15T07:07:04Z 置信度 0.70
• Democratizing Federated Learning: “FL-Insight” as an Interactive Visual Demonstrator for SME Adoption
  crossref Thomas Van Den Bossche, Laurens Van De Perre, Abasin Abdul Khalil 2026-01-20T20:38:34Z 置信度 0.70