隐私计算与数据要素 · 全部实体（第 68 / 100 页）

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• Faster Secure Data Mining Framework via Homomorphic Encryption
  crossref 2024-08-28T10:21:23Z 置信度 0.70
• Global Model Privacy Protection Mechanism in Federated Learning
  crossref Ajit Kumar, Bong Jun Choi 2024-07-03T17:25:55Z 置信度 0.70
• Innovative Solutions
  crossref Raj Kishor Verma, Kaushal Kishor 2024-09-20T17:25:42Z 置信度 0.70
• Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review
  crossref Ferial ElRobrini, Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Nedaa Al-Tawalbeh 等 2024-11-17T15:52:56Z 置信度 0.70
• FreeFL: Privacy-Preserving Cross-Silo Federated Learning without Third Party
  Cross-silo federated learning (FL) allows organizations to collaboratively train machine learning (ML) models by aggregating local gradients from clients without sharing their training data. Despite its merits, it suffers from privacy concerns due to the leaka…
  crossref Fucai Luo, Jiahui Wu, Haiyan Wang, Xingfu Yan 2024-12-05T00:53:40Z 置信度 0.70
• SAFARI: Self-regulAted Clustered FederAted Learning in a HeteRogeneous EnvIronment
  crossref Sai Puppala, Ismail Hossain, Md Jahangir Alam, Sajedul Talukder 2025-03-04T18:39:11Z 置信度 0.70
• A Federated Semi-Supervised Learning Framework for Vehicular Networks
  crossref Jiachen Liu, Jianfeng Yang, Jianling Hu, Tianqi Yu 2024-07-24T06:20:54Z 置信度 0.70
• Edge-Cloud Computing and Federated-Split Learning in the Internet of Things
  crossref 2024-09-23T05:26:54Z 置信度 0.70
• Artificial Intelligence Using Federated Learning
  crossref Ahmed A Elngar, Diego Oliva, Valentina E. Balas 2024-11-29T17:15:57Z 置信度 0.70
• ENHANCING IMAGE CLASSIFICATION WITH FEDERATED LEARNING: A COMPARATIVE STUDY OF VGG16 AND MOBILENET ON CIFAR-10
  In this project, I explored the application of federated learning (FL) algorithms in enhancing image classification tasks using the CIFAR-10 dataset, with a focus on the VGG16 and MobileNet architectures. The project compared the efficacy of various FL algorit…
  crossref Ehsan Alam 2024-05-15T19:35:30Z 置信度 0.70
• Learned Model Compression for Efficient and Privacy-Preserving Federated Learning
  crossref Yiming Chen, Lusine Abrahamyan, Hichem Sahli, Nikos Deligiannis 2024-03-18T00:26:21Z 置信度 0.70
• Multi-Model based Federated Learning Against Model Poisoning Attack: A Deep Learning Based Model Selection for MEC Systems
  crossref Somayeh Kianpisheh, Chafika Benzaïd, Tarik Taleb 2025-03-11T17:30:35Z 置信度 0.70
• Message from the General Chairs
  crossref Schahram Dustdar, Omer Rana 2025-01-21T18:22:35Z 置信度 0.70
• Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
  crossref Sijia Chen, Ningxin Su, Baochun Li 2024-08-22T17:43:37Z 置信度 0.70
• FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data
  crossref Ahmed Anwar, Brian Moser, Dayananda Herurkar, Federico Raue 等 2025-01-21T18:22:35Z 置信度 0.70
• Personalized Federated Learning with Contextual Modulation and Meta-Learning
  crossref Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn Rögnvaldsson 2024-04-11T07:07:02Z 置信度 0.70
• Federated Learning for Privacy-Preserving Machine Learning in IoT Networks
  crossref G Anitha, A. Jegatheesan 2024-10-04T17:33:05Z 置信度 0.70
• Lightweight Federated Learning based White Space Detector for Cognitive Radios
  crossref Md Mehedi Hassan Galib, Mohamed Younis 2025-03-11T17:30:35Z 置信度 0.70
• One-Shot Clustering for Federated Learning
  crossref Maciej Krzysztof Zuziak, Roberto Pellungrini, Salvatore Rinzivillo 2025-01-16T18:31:23Z 置信度 0.70
• Cooperative Gradient Coding for Semi-Decentralized Federated Learning
  crossref Shudi Weng, Chengxi Li, Ming Xiao, Mikael Skoglund 2025-03-11T17:30:35Z 置信度 0.70
• Mobility-Aware Federated Learning-based Proactive UAVs Placement in Emerging Cellular Networks
  With the vast proliferation of smart mobile devices, there is an ever-increasing demand for higher data rates and seamless connectivity throughout. Current 5th generation and beyond (B5G) cellular networks struggle to eradicate outage zones and ensure seamless…
  crossref Sanaullah Manzoor, Mazen Hasna, Muhammad Zeeshan Shakir 2024-03-30T00:34:30Z 置信度 0.70
• Empowering Smart Cities through Federated Learning An Overview
  crossref Ayah Jarour 2024-11-11T18:37:56Z 置信度 0.70
• Prompt Tuning Empowering Downstream Tasks in Multimodal Federated Learning
  crossref Yichen Bao 2024-12-12T19:07:29Z 置信度 0.70
• A Differentially Private Federated Learning Application in Privacy-Preserving Medical Imaging
  Abstract This research addresses the escalating concerns surrounding privacy, particularly in the context of safeguarding sensitive medical data within the increasingly demanding healthcare landscape. We undertake an experimental exploration of differentially …
  crossref Mohamad HAJ FARES, Ahmet SERTBAŞ 2024-01-18T11:10:16Z 置信度 0.70
• FL-CycleGAN: Enhancing Mobile Photography with Federated Learning-Enabled CycleGAN
  crossref Ramindu Walgama, K.T. Yasas Mahima 2024-09-30T17:24:20Z 置信度 0.70
• Personalized Federated Learning with Multi-Server
  crossref Yunzi Huang, Haifeng Dai, Guanqiao Kong, Jing Nie 2025-05-19T17:52:05Z 置信度 0.70
• Optimal Client Selection for Wireless Federated Learning
  crossref Heng An, Cuitao Zhu 2024-12-30T19:19:13Z 置信度 0.70
• Federated Learning
  crossref Lukas Willburger 2024-12-10T16:36:23Z 置信度 0.70
• Federated Learning Incorporating Non-Orthogonal Transmission and Unstructured Model Pruning
  crossref Siyu Gao, Ming Zhao, Shengli Zhou 2025-03-11T17:30:35Z 置信度 0.70
• Federated Learning: Catalyzing the Next AI Breakthrough
  crossref Daniel J. Beutel 2024-12-11T22:22:43Z 置信度 0.70
• Cloud-based Federated Learning Framework for MRI Segmentation
  crossref Rukesh Prajapati, Amr S. El-Wakeel 2024-08-20T15:34:42Z 置信度 0.70
• Gradient Guard: Robust Federated Learning using Saliency Maps
  crossref Yeshwanth Nagaraj, Ujjwal Gupta 2024-05-06T17:20:54Z 置信度 0.70
• Federated Learning-Based Privacy Protection Methods for Internet of Things Systems
  The Internet of Things (IoT) forms intelligent systems, such as smart cities and factories, to enhance productivity and provide revolutionary and automated services to end-users and organisations. An IoT ecosystem requires more dynamics and heterogeneity with …
  crossref Mahmuda Akter, Nour Moustafa 2024-07-07T13:51:27Z 置信度 0.70
• A Federated Meta-Reinforcement Learning Algorithm Based on Gradient Correction
  crossref Zerui Qin, Sheng Yue 2024-07-30T22:26:48Z 置信度 0.70
• Federated Learning for Seismic Data Denoising: Privacy-Preserving Paradigm
  Summary Federated Learning (FL) is a framework that empowers multiple clients to develop robust machine learning (ML) algorithms while safeguarding data privacy and security. This paper's primary goal is to investigate the capability of the FL framework in pre…
  crossref Kamalesh Kumar Mandakolathur Guruprasad, Gayatri Sunil Ambulkar, Geetha Nair 2024-02-27T22:59:19Z 置信度 0.70
• Introduction to AI, ML, Federated Learning, and LLM in Software Engineering
  This research investigates the transformative intersection of artificial intelligence (AI), machine learning (ML), federated learning, and large language models (LLM) within the realm of Software Engineering. The study contextualizes the historical evolution o…
  crossref Pawan Kumar Goel 2024-05-02T09:03:18Z 置信度 0.70
• The Evolution of Machine Learning: From Centralized to Distributed
  crossref Jayakrushna Sahoo, Akarsh K. Nair, Richa Sharma 2024-05-30T10:30:21Z 置信度 0.70
• A Cloud Edge Federated Data Center Balanced Optimization Scheduling Algorithm Combining Deep Reinforcement Learning and Pso
  crossref Xiuniao Zhao 2024-01-10T19:56:08Z 置信度 0.70
• Federated Learning for Private AI Diagnosis of Schizophrenia
  This study delves into the realm of federated learning, focusing on its application in the private and accurate artificial intelligence (AI) diagnosis of schizophrenia. Leveraging the collaborative power of distributed datasets without compromising individual …
  crossref ­ Kunal, Santosh Kumar Sahu, Mohammed Azam, Manuj Takkar 等 2024-05-02T09:01:10Z 置信度 0.70
• Swarm Split Learning: A Fully Distributed Machine Learning System for Energy-Constrained IoT Systems
  crossref Ahmad Ayad, Tim Bauerle, Mahdi Barhoush, Anke Schmeink 2025-01-21T18:22:35Z 置信度 0.70
• Federated Learning for Network Traffic Prediction
  crossref Sadananda Behera, Saroj Kumar Panda, Tania Panayiotou, Georgios Ellinas 2024-08-15T17:18:52Z 置信度 0.70
• Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning
  Recent methods leverage a hypernet to handle the performance-fairness trade-offs in federated learning. This hypernet maps the clients' preferences between model performance and fairness to preference-specifc models on the trade-off curve, known as local Paret…
  crossref Rongguang Ye, Ming Tang 2024-07-26T10:28:11Z 置信度 0.70
• Keynote Speech 4 Federated Learning for IoT
  crossref Daniel J. Beutel 2024-10-14T17:22:38Z 置信度 0.70
• Maximizing Privacy in Reinforcement Learning with Federated Approaches
  crossref Shiva Mehta, Sumeet Singh Sarpal 2024-08-15T13:21:37Z 置信度 0.70
• A state-of-the-art on federated learning for vehicular communications
  crossref Drissi Maroua 2023-12-02T11:23:26Z 置信度 0.70
• Fedelr: When Federated Learning Meets Learning with Noisy Labels
  crossref Ruizhi Pu, Lixing Yu, Shaojie Zhan, Gezheng Xu 等 2024-10-22T15:02:37Z 置信度 0.70
• Wireless Channel Estimation using Federated Learning
  crossref Jasneet Kaur, M. Arif Khan 2024-06-10T17:19:31Z 置信度 0.70
• Energy-Aware Federated Learning in Satellite Constellations
  crossref Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski 2025-08-12T17:51:39Z 置信度 0.70
• Personalized Federated Learning with Optimized Contrastive Learning for Intrusion Detection System
  crossref Quan Hong Ngo, Van T.B Pham, Ly Vu 2025-05-28T17:50:04Z 置信度 0.70
• Decentralized Federated Learning over Satellite Networks (Dec-FLSat): A Learning Scheme Based on LEO-Structure
  crossref Mohanad Obeed, Gunes Karabulut Kurt, Halim Yanikomeroglu 2025-03-11T17:30:35Z 置信度 0.70
• Federated Learning on Knowledge Graph Embeddings via Contrastive Alignment
  crossref Antor Mahmud, Renata Dividino 2025-01-16T18:31:23Z 置信度 0.70
• Personalized federated meta-learning based on dynamic clustering
  crossref Qingqing Sun 2025-03-04T18:39:08Z 置信度 0.70
• Harnessing Distributed Computing Resources with Federated Reinforcement Learning
  crossref Shiva Mehta, Savinder Kaur 2025-01-21T18:22:34Z 置信度 0.70
• Federated Learning Based on Feature Fusion
  crossref Junjie Cao, Zhiyu Chen 2024-04-22T17:33:49Z 置信度 0.70
• Secure Submodel Aggregation for Resource-Aware Federated Learning
  crossref Hasin Us Sami, Başak Güler 2024-08-19T13:25:01Z 置信度 0.70
• Machine learning in distributed, federated and non-stationary environments - recent trends
  crossref Mirko Polato, Barbara Hammer, Frank-Michael Schleif 2024-09-09T13:23:50Z 置信度 0.70
• Federated Learning Poisoning Attack Detection: Reconfiguration Algorithm TopK-FLcredit
  crossref Zhang Hong, Li Hongjiao 2024-04-15T17:28:24Z 置信度 0.70
• Efficient Federated Learning Through Distributed Model Pruning
  crossref Mohammad Munzurul Islam, Mohammed Alawad 2024-09-25T17:27:50Z 置信度 0.70
• Differentially Private federated learning to Protect Identity in Stress Recognition
  crossref Bouchiba GUELTA 2024-06-13T12:33:03Z 置信度 0.70
• Towards Federated Learning by Kernels
  crossref Kilho Shin, Takenobu Seito, Chris Liu 2024-05-21T17:20:52Z 置信度 0.70
• Revolutionizing Emotion-Driven Sentiment Analysis using Federated Learning on Edge Devices for Superior Privacy and Performance
  crossref 2024-08-19T04:09:25Z 置信度 0.70
• Predicting Online Consumer Credit Default Using Mobile Data Based on Federated Learning
  crossref Fan Wang, Yunpeng Zhang, Lijian Wei 2024-11-16T17:39:07Z 置信度 0.70
• Federated Learning for Privacy Preservation in Healthcare
  This chapter delves into fundamental concepts of privacy preservation and federated learning (FL) in healthcare. Emphasizing the importance of privacy in healthcare data, it explores ethical and regulatory considerations surrounding sensitive patient informati…
  crossref Hari Kishan Kondaveeti, Chinna Gopi Simhadri, Srileakhana Mangapathi, Valli Kumari Vatsavayi 2024-05-02T09:01:10Z 置信度 0.70
• Network Traffic Anomaly Detection Based on Federated Learning
  crossref Yi Luan 2024-04-22T17:33:49Z 置信度 0.70
• Movable Antenna Design for UAV-Aided Federated Learning via Deep Reinforcement Learning
  crossref Mohsen Ahmadzadeh, Saeid Pakravan, Ghosheh Abed Hodtani 2025-02-26T13:43:34Z 置信度 0.70
• Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
  crossref Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda 等 2025-11-03T11:20:56Z 置信度 0.70
• Federated Learning for Private Cancer Diagnosis With Exascale Computing
  This study delves into the intersection of federated learning, privacy preservation, and exascale computing to advance the field of cancer diagnosis. Employing a federated learning framework, the research addresses the imperative need for collaborative, yet pr…
  crossref N. R. Vembu, Niladri Maiti, K. Kadiervel, Amarendranath Choudhury 等 2024-05-02T09:01:10Z 置信度 0.70
• Owl:Worker-Assisted Server Bandwidth Optimization for Efficient Communication Federated Learning
  Edge computing in federated learning based on centralized architecture often faces communication constraints in large clusters. Although there have been some efforts like computation-communication overlapping and fine-granularity flow scheduling towards how to…
  crossref Xiaoming Han, Boan Liu, Chuang Hu, Dazhao Cheng 2024-08-05T15:21:20Z 置信度 0.70
• Federated Zero-Shot Learning with Mid-Level Semantic Knowledge Transfer
  crossref Shitong Sun, Chenyang Si, Guile Wu, Shaogang Gong 2024-02-29T21:22:12Z 置信度 0.70
• Multi-Level Analyzation of Imbalance to Resolve Non-Iid-Ness in Federated Learning
  crossref Haengbok Chung, Jae Sung Lee 2024-07-15T11:55:48Z 置信度 0.70
• Secure Fair Aggregation Based on Category Grouping in Federated Learning
  crossref Jie Zhou, Jinlin Hu, Jiajun Xue, Shengke Zeng 2024-06-21T16:51:31Z 置信度 0.70
• Beyond Data Sharing: Enhancing Iot Intrusion Detection with Blockchain-Enabled Federated Learning
  crossref Aditya Durgadas Naik, Raj Mani Shukla 2024-12-06T19:43:27Z 置信度 0.70
• Federated Learning-Based Spectrum and Energy Efficiency Enhancement in Hap-Assisted Leo Satellite Communication
  crossref Sengly Muy, JungRyun Lee 2024-12-18T21:38:22Z 置信度 0.70
• Entropy and Mobility-Based Model Assignment for Multi-Model Vehicular Federated Learning
  crossref Wellington Lobato, Joahannes B. D. Da Costa, Luis F. G. Gonzalez, Eduardo Cerqueira 等 2025-01-21T18:22:35Z 置信度 0.70
• Federated Learning: Bridging Data Privacy and <scp>AI</scp> Advancements
  crossref D. Sumathi, Likitha Chowdary Botta, Mure Sai Jaideep Reddy, Avi Das 2024-11-22T21:19:26Z 置信度 0.70
• Retracted: Leveraging Machine Learning for Enhanced SensorPowered Green IoT with Federated Learning
  crossref Rekha Devrani, R Premkumar, Shyam Kumar 2024-11-04T18:06:46Z 置信度 0.70
• Enhancing Image Classification With Federated Learning: a Comparative Study of VGG16 and Mobilenet on CIFAR-10
  In this project, I explored the application of federated learning (FL) algorithms in enhancing image classification tasks using the CIFAR-10 dataset, with a focus on the VGG16 and MobileNet architectures. The project compared the efficacy of various FL algorit…
  crossref Ehsan Alam 2024-05-22T12:29:31Z 置信度 0.70
• Contract Design for Adaptive Federated Learning
  crossref Ni Yang, Yue Cui, Man Hon Cheung 2025-03-11T17:30:35Z 置信度 0.70
• Survey Optimizing Reinforcement Learning, Federated Learning, and Computational Network Model Performance
  crossref Sarah H. Mnkash, Faiz A. Al Alawv, Israa T. Ali 2025-01-10T20:02:20Z 置信度 0.70
• Enhancing computational performance in healthcare through federated learning approach
  crossref Farzeen Ashfaq, N.Z. Jhanjhi, Navid Ali Khan, Sayan Kumar Ray 等 2024-10-04T08:10:23Z 置信度 0.70
• Revolutionizing Healthcare
  crossref Renu Vij 2024-07-29T08:04:57Z 置信度 0.70
• Federated Query Processing for Data Integration Using Semantic Web Technologies
  crossref Nidhi Gupta, Pawan Verma, Monali Gulhane, Nitin Rakesh 等 2024-11-29T17:15:57Z 置信度 0.70
• FedTAIL: A Federated Learning Approach with Trans-Architecture Intermediate Links
  crossref Dian Jiao, Jie Liu 2024-09-09T17:35:05Z 置信度 0.70
• BadVFL: Backdoor Attacks in Vertical Federated Learning
  crossref Mohammad Naseri, Yufei Han, Emiliano De Cristofaro 2024-09-05T13:56:32Z 置信度 0.70
• Membershield: A Framework for Federated Learning with Membership Privacy
  crossref Faisal Ahmed, David Sánchez, Zouhair Haddi, Josep Domingo-Ferrer 2024-04-03T02:18:29Z 置信度 0.70
• Exploration and Analysis of FedAvg, FedProx, FedMA, MOON, and FedProc Algorithms in Federated Learning
  crossref Jinlin Li 2024-08-07T17:09:50Z 置信度 0.70
• A Comprehensive Survey on Client Selection Strategies in Federated Learning
  crossref Jian Li, Tongbao Chen, Shaohua Teng 2024-06-11T05:19:15Z 置信度 0.70
• A Federated Learning Client Selection Method via Multi-Task Deep Reinforcement Learning
  crossref Le Hou, Laisen Nie, Xinyang Deng 2025-01-22T18:45:23Z 置信度 0.70
• Federated Learning with Privacy-Preserving Active Learning: A Min-Max Mutual Information Approach
  crossref Zahir Alsulaimawi 2024-03-20T18:12:10Z 置信度 0.70
• Federated learning enabled digital twins for Industry 5.0: perspectives, challenges, and future directions
  crossref Dasaradharami Reddy Kandati, Supriya Y, Gokul Yenduri, Praveen Kumar Reddy Maddikunta 等 2025-01-13T08:38:15Z 置信度 0.70
• Federated learning in medical education in Industry 5.0
  crossref Y. Supriya, Dasari Bhulakshmi, Sweta Bhattacharya, Thippa Reddy Gadekallu 等 2025-01-13T08:38:15Z 置信度 0.70
• Front Matter
  crossref 2024-10-04T08:10:23Z 置信度 0.70
• Out-of-Distribution Detection Via Outlier Exposure in Federated Learning
  crossref Gu-Bon Jeong, Dong-Wan Choi 2024-05-29T03:17:52Z 置信度 0.70
• Federated Learning-Based Distributed Model Predictive Control of Nonlinear Systems
  crossref Zeyuan Xu, Zhe Wu 2024-09-05T17:56:19Z 置信度 0.70
• SemiS-VFL: A Semi-Supervised Machine Learning Frameworkfor Vertical Federated Learning
  crossref Kun Yan, Paula Branco 2026-01-31T18:26:17Z 置信度 0.70
• FLARE: Federated Learning And Resilient Encryption for Firewalls
  crossref Lohith Senthilkumar, Aaditya Rengarajan 2025-02-27T18:42:58Z 置信度 0.70
• Enhancing Federated Learning-Based Social Recommendations with Graph Attention Networks
  crossref Zhihui Xu, Bing Li, Wenming Cao 2024-10-07T15:01:13Z 置信度 0.70
• Federated Learning for Radar Systems - Sharing Knowledge without sharing Data
  crossref Simon Wagner, Stefan Brüggenwirth 2025-05-14T13:30:46Z 置信度 0.70
• Enhancing data privacy in federated learning using artificial intelligence
  Federated Learning (FL) is a decentralised approach to machine learning that enables model training on local devices without the need to share raw data. While FL inherently provides some level of privacy, significant challenges remain in fully protecting sensi…
  crossref Piyush Dua 2024-10-16T21:26:45Z 置信度 0.70
• Federated learning in healthcare applications
  crossref Prasad Kanhegaonkar, Surya Prakash 2024-03-15T05:12:37Z 置信度 0.70