Journal articles on the topic 'Federated learning applications'
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Saha, Sudipan, and Tahir Ahmad. "Federated transfer learning: Concept and applications." Intelligenza Artificiale 15, no. 1 (July 28, 2021): 35–44. http://dx.doi.org/10.3233/ia-200075.
Full textLaunet, Laëtitia, Yuandou Wang, Adrián Colomer, Jorge Igual, Cristian Pulgarín-Ospina, Spiros Koulouzis, Riccardo Bianchi, et al. "Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions." Applied Sciences 13, no. 2 (January 9, 2023): 919. http://dx.doi.org/10.3390/app13020919.
Full textBenedict, Shajulin, Deepumon Saji, Rajesh P. Sukumaran, and Bhagyalakshmi M. "Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications." September 2021 3, no. 3 (August 30, 2021): 196–217. http://dx.doi.org/10.36548/jaicn.2021.3.004.
Full textLi, Li, Yuxi Fan, Mike Tse, and Kuo-Yi Lin. "A review of applications in federated learning." Computers & Industrial Engineering 149 (November 2020): 106854. http://dx.doi.org/10.1016/j.cie.2020.106854.
Full textAmiri, Mohammad Mohammadi, Tolga M. Duman, Deniz Gunduz, Sanjeev R. Kulkarni, and H. Vincent Poor Poor. "Blind Federated Edge Learning." IEEE Transactions on Wireless Communications 20, no. 8 (August 2021): 5129–43. http://dx.doi.org/10.1109/twc.2021.3065920.
Full textFu, Xingbo, Binchi Zhang, Yushun Dong, Chen Chen, and Jundong Li. "Federated Graph Machine Learning." ACM SIGKDD Explorations Newsletter 24, no. 2 (November 29, 2022): 32–47. http://dx.doi.org/10.1145/3575637.3575644.
Full textLiu, Yang, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, and Qiang Yang. "FedVision: An Online Visual Object Detection Platform Powered by Federated Learning." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 08 (April 3, 2020): 13172–79. http://dx.doi.org/10.1609/aaai.v34i08.7021.
Full textMun, Hyunsu, and Youngseok Lee. "Internet Traffic Classification with Federated Learning." Electronics 10, no. 1 (December 28, 2020): 27. http://dx.doi.org/10.3390/electronics10010027.
Full textYang, Qiang. "Toward Responsible AI: An Overview of Federated Learning for User-centered Privacy-preserving Computing." ACM Transactions on Interactive Intelligent Systems 11, no. 3-4 (December 31, 2021): 1–22. http://dx.doi.org/10.1145/3485875.
Full textYang, Zhaohui, Mingzhe Chen, Kai-Kit Wong, H. Vincent Poor, and Shuguang Cui. "Federated Learning for 6G: Applications, Challenges, and Opportunities." Engineering 8 (January 2022): 33–41. http://dx.doi.org/10.1016/j.eng.2021.12.002.
Full textHu, Sixu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, and Bingsheng He. "The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems." ACM Transactions on Intelligent Systems and Technology 13, no. 4 (August 31, 2022): 1–32. http://dx.doi.org/10.1145/3510540.
Full textThorgeirsson, Adam Thor, and Frank Gauterin. "Probabilistic Predictions with Federated Learning." Entropy 23, no. 1 (December 30, 2020): 41. http://dx.doi.org/10.3390/e23010041.
Full textMansouri, Mohamad, Melek Önen, Wafa Ben Jaballah, and Mauro Conti. "SoK: Secure Aggregation Based on Cryptographic Schemes for Federated Learning." Proceedings on Privacy Enhancing Technologies 2023, no. 1 (January 2023): 140–57. http://dx.doi.org/10.56553/popets-2023-0009.
Full textYan, Xin, Yiming Qin, Xiaodong Hu, and Xiaoling Xiao. "Distributed consensus problem with caching on federated learning framework." International Journal of Distributed Sensor Networks 18, no. 4 (April 2022): 155013292210929. http://dx.doi.org/10.1177/15501329221092932.
Full textLiu, Yang, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, and Qiang Yang. "Federated Learning-Powered Visual Object Detection for Safety Monitoring." AI Magazine 42, no. 2 (October 20, 2021): 19–27. http://dx.doi.org/10.1609/aimag.v42i2.15095.
Full textKim, Seong-Woong, and Dong-Wan Choi. "Stable Federated Learning with Dataset Condensation." Journal of Computing Science and Engineering 16, no. 1 (March 31, 2022): 52–62. http://dx.doi.org/10.5626/jcse.2022.16.1.52.
Full textKim, Hyesung, Jihong Park, Mehdi Bennis, and Seong-Lyun Kim. "Blockchained On-Device Federated Learning." IEEE Communications Letters 24, no. 6 (June 2020): 1279–83. http://dx.doi.org/10.1109/lcomm.2019.2921755.
Full textZhu, Hangyu, and Yaochu Jin. "Multi-Objective Evolutionary Federated Learning." IEEE Transactions on Neural Networks and Learning Systems 31, no. 4 (April 2020): 1310–22. http://dx.doi.org/10.1109/tnnls.2019.2919699.
Full textZellinger, Werner, Volkmar Wieser, Mohit Kumar, David Brunner, Natalia Shepeleva, Rafa Gálvez, Josef Langer, Lukas Fischer, and Bernhard Moser. "Beyond federated learning: On confidentiality-critical machine learning applications in industry." Procedia Computer Science 180 (2021): 734–43. http://dx.doi.org/10.1016/j.procs.2021.01.296.
Full textNawrin Tabassum, Mustofa Ahmed, Nushrat Jahan Shorna, MD Mejbah Ur Rahman Sowad, and H M Zabir Haque. "Depression Detection Through Smartphone Sensing: A Federated Learning Approach." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 01 (January 10, 2023): 40–56. http://dx.doi.org/10.3991/ijim.v17i01.35131.
Full textPrayitno, Chi-Ren Shyu, Karisma Trinanda Putra, Hsing-Chung Chen, Yuan-Yu Tsai, K. S. M. Tozammel Hossain, Wei Jiang, and Zon-Yin Shae. "A Systematic Review of Federated Learning in the Healthcare Area: From the Perspective of Data Properties and Applications." Applied Sciences 11, no. 23 (November 25, 2021): 11191. http://dx.doi.org/10.3390/app112311191.
Full textKang, Jiawen, Zehui Xiong, Dusit Niyato, Yuze Zou, Yang Zhang, and Mohsen Guizani. "Reliable Federated Learning for Mobile Networks." IEEE Wireless Communications 27, no. 2 (April 2020): 72–80. http://dx.doi.org/10.1109/mwc.001.1900119.
Full textPham, Quoc-Viet, Ming Zeng, Thien Huynh-The, Zhu Han, and Won-Joo Hwang. "Aerial Access Networks for Federated Learning: Applications and Challenges." IEEE Network 36, no. 3 (May 2022): 159–66. http://dx.doi.org/10.1109/mnet.013.2100311.
Full textBanabilah, Syreen, Moayad Aloqaily, Eitaa Alsayed, Nida Malik, and Yaser Jararweh. "Federated learning review: Fundamentals, enabling technologies, and future applications." Information Processing & Management 59, no. 6 (November 2022): 103061. http://dx.doi.org/10.1016/j.ipm.2022.103061.
Full textShaheen, Momina, Muhammad Shoaib Farooq, Tariq Umer, and Byung-Seo Kim. "Applications of Federated Learning; Taxonomy, Challenges, and Research Trends." Electronics 11, no. 4 (February 21, 2022): 670. http://dx.doi.org/10.3390/electronics11040670.
Full textStallmann, Morris, and Anna Wilbik. "On a Framework for Federated Cluster Analysis." Applied Sciences 12, no. 20 (October 17, 2022): 10455. http://dx.doi.org/10.3390/app122010455.
Full textJang, Suyeon, Hyun Woo Oh, Young Hyun Yoon, Dong Hyun Hwang, Won Sik Jeong, and Seung Eun Lee. "A Multi-Core Controller for an Embedded AI System Supporting Parallel Recognition." Micromachines 12, no. 8 (July 21, 2021): 852. http://dx.doi.org/10.3390/mi12080852.
Full textShamim, Rejuwan, Md Arshad, and Dr Vinay Pandey. "A Machine Learning Model to Protect Privacy Using Federal Learning with Homomorphy Encryption." International Journal for Research in Applied Science and Engineering Technology 10, no. 10 (October 31, 2022): 989–94. http://dx.doi.org/10.22214/ijraset.2022.47120.
Full textAmiri, Mohammad Mohammadi, and Deniz Gunduz. "Federated Learning Over Wireless Fading Channels." IEEE Transactions on Wireless Communications 19, no. 5 (May 2020): 3546–57. http://dx.doi.org/10.1109/twc.2020.2974748.
Full textYang, Xiaohui, and Zijian Dong. "Kalman Filter-Based Differential Privacy Federated Learning Method." Applied Sciences 12, no. 15 (August 2, 2022): 7787. http://dx.doi.org/10.3390/app12157787.
Full textBemani, Ali, and Niclas Björsell. "Aggregation Strategy on Federated Machine Learning Algorithm for Collaborative Predictive Maintenance." Sensors 22, no. 16 (August 19, 2022): 6252. http://dx.doi.org/10.3390/s22166252.
Full textLiu, Yejia, Weiyuan Wu, Lampros Flokas, Jiannan Wang, and Eugene Wu. "Enabling SQL-based training data debugging for federated learning." Proceedings of the VLDB Endowment 15, no. 3 (November 2021): 388–400. http://dx.doi.org/10.14778/3494124.3494125.
Full textOh, Seungeun, Jihong Park, Eunjeong Jeong, Hyesung Kim, Mehdi Bennis, and Seong-Lyun Kim. "Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup." IEEE Communications Letters 24, no. 10 (October 2020): 2211–15. http://dx.doi.org/10.1109/lcomm.2020.3003693.
Full textElbir, Ahmet M., Anastasios K. Papazafeiropoulos, and Symeon Chatzinotas. "Federated Learning for Physical Layer Design." IEEE Communications Magazine 59, no. 11 (November 2021): 81–87. http://dx.doi.org/10.1109/mcom.101.2100138.
Full textChen, Mingzhe, H. Vincent Poor, Walid Saad, and Shuguang Cui. "Wireless Communications for Collaborative Federated Learning." IEEE Communications Magazine 58, no. 12 (December 2020): 48–54. http://dx.doi.org/10.1109/mcom.001.2000397.
Full textZhan, Yufeng, Peng Li, Zhihao Qu, Deze Zeng, and Song Guo. "A Learning-Based Incentive Mechanism for Federated Learning." IEEE Internet of Things Journal 7, no. 7 (July 2020): 6360–68. http://dx.doi.org/10.1109/jiot.2020.2967772.
Full textXu, Bin, Sheng Yan, Shuai Li, and Yidi Du. "A Federated Transfer Learning Framework Based on Heterogeneous Domain Adaptation for Students’ Grades Classification." Applied Sciences 12, no. 21 (October 22, 2022): 10711. http://dx.doi.org/10.3390/app122110711.
Full textRincon, Jaime, Vicente Julian, and Carlos Carrascosa. "FLaMAS: Federated Learning Based on a SPADE MAS." Applied Sciences 12, no. 7 (April 6, 2022): 3701. http://dx.doi.org/10.3390/app12073701.
Full textNasiri, Sara, Iman Nasiri, and Kristof Van Laerhoven. "Wearable xAI: A Knowledge-Based Federated Learning Framework." Engineering Proceedings 6, no. 1 (May 17, 2021): 79. http://dx.doi.org/10.3390/i3s2021dresden-10143.
Full textChen, Hao, Ming Xiao, and Zhibo Pang. "Satellite-Based Computing Networks with Federated Learning." IEEE Wireless Communications 29, no. 1 (February 2022): 78–84. http://dx.doi.org/10.1109/mwc.008.00353.
Full textYang, Qiang, Yongxin Tong, Yang Liu, Yangqiu Song, Hao Peng, and Boi Faltings. "Preface to Federated Learning: Algorithms, Systems, and Applications: Part 2." ACM Transactions on Intelligent Systems and Technology 13, no. 5 (October 31, 2022): 1–2. http://dx.doi.org/10.1145/3536420.
Full textCrowson, Matthew G., Dana Moukheiber, Aldo Robles Arévalo, Barbara D. Lam, Sreekar Mantena, Aakanksha Rana, Deborah Goss, David W. Bates, and Leo Anthony Celi. "A systematic review of federated learning applications for biomedical data." PLOS Digital Health 1, no. 5 (May 19, 2022): e0000033. http://dx.doi.org/10.1371/journal.pdig.0000033.
Full textXiao, Bin, Qingzhen Xu, Chengying He, and Jianwu Lin. "Blockchain and Federated Learning Based Bidding Applications in Power Markets." Procedia Computer Science 202 (2022): 21–26. http://dx.doi.org/10.1016/j.procs.2022.04.004.
Full textGuberović, Emanuel, Charalampos Alexopoulos, Ivana Bosnić, and Igor Čavrak. "Framework for Federated Learning Open Models in e-Government Applications." Interdisciplinary Description of Complex Systems 20, no. 2 (April 28, 2022): 162–78. http://dx.doi.org/10.7906/indecs.20.2.8.
Full textRahman, K. M. Jawadur, Faisal Ahmed, Nazma Akhter, Mohammad Hasan, Ruhul Amin, Kazi Ehsan Aziz, A. K. M. Muzahidul Islam, Md Saddam Hossain Mukta, and A. K. M. Najmul Islam. "Challenges, Applications and Design Aspects of Federated Learning: A Survey." IEEE Access 9 (2021): 124682–700. http://dx.doi.org/10.1109/access.2021.3111118.
Full textAledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Fahad Saeed. "Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications." IEEE Access 8 (2020): 140699–725. http://dx.doi.org/10.1109/access.2020.3013541.
Full textOtoum, Yazan, Vinay Chamola, and Amiya Nayak. "Federated and Transfer Learning-Empowered Intrusion Detection for IoT Applications." IEEE Internet of Things Magazine 5, no. 3 (September 2022): 50–54. http://dx.doi.org/10.1109/iotm.001.2200048.
Full textVictor, Nancy, Rajeswari Chengoden, Mamoun Alazab, Sweta Bhattacharya, Sindri Magnusson, Praveen Kumar Reddy Maddikunta, Kadiyala Ramana, and Thippa Reddy Gadekallu. "Federated Learning for IoUT: Concepts, Applications, Challenges and Future Directions." IEEE Internet of Things Magazine 5, no. 4 (December 2022): 36–41. http://dx.doi.org/10.1109/iotm.001.2200067.
Full textAbreha, Haftay Gebreslasie, Mohammad Hayajneh, and Mohamed Adel Serhani. "Federated Learning in Edge Computing: A Systematic Survey." Sensors 22, no. 2 (January 7, 2022): 450. http://dx.doi.org/10.3390/s22020450.
Full textPeng, Yongqiang, Zongyao Chen, Zexuan Chen, Wei Ou, Wenbao Han, and Jianqiang Ma. "BFLP: An Adaptive Federated Learning Framework for Internet of Vehicles." Mobile Information Systems 2021 (March 2, 2021): 1–18. http://dx.doi.org/10.1155/2021/6633332.
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