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Publication search results
found 45 matches
- 2023
- Muzammil Ahmed, Ahmed B. Altamimi, Wilayat Khan, Mohammad Salih Alsaffar, Aakash Ahmad, Zawar H. Khan, Abdulrahman Alreshidi:
PhishCatcher: Client-Side Defense Against Web Spoofing Attacks Using Machine Learning. IEEE Access 11: 61249-61263 (2023) - Artrim Kjamilji, Osman Berke Güney:
Highly efficient secure linear algebra for private machine learning classifications over malicious clients in the post-quantum world. J. King Saud Univ. Comput. Inf. Sci. 35(9): 101718 (2023) - Dilruba Showkat, Angela D. R. Smith, Lingqing Wang, Alexandra To:
"Who is the right homeless client?": Values in Algorithmic Homelessness Service Provision and Machine Learning Research. CHI 2023: 394:1-394:21 - Saki Takano, Akihiro Nakao, Saneyasu Yamaguchi, Masato Oguchi:
Secure Feedback to Edge Servers in Distributed Machine Learning Using Rich Clients. COMPSAC 2023: 934-939 - Siddharth Dhama, Nadeem Akhtar, Preyas Hathi, Samar Agnihotri:
Downlink SNR Estimation of Wi-Fi Clients using Machine Learning. COMSNETS 2023: 410-413 - Ahmed M. Abdelmoniem, Yomna M. Abdelmoniem, Ahmed Elzanaty:
A2FL: Availability-Aware Selection for Machine Learning on Clients with Federated Big Data. ICC 2023: 1200-1205 - Guan Qiang, Fang Fang, Xianbin Wang:
Security and Efficiency Enhancement for Split Learning: A Machine Learning based Malicious Clients Detection Approach. PIMRC 2023: 1-6 - 2022
- Jasneet Kaur, M. Arif Khan:
Federation based joint client and server side Machine Learning for 5G and beyond Wireless Channel Estimation. Comput. Networks 209: 108902 (2022) - Renjie Gu, Chaoyue Niu, Fan Wu, Guihai Chen, Chun Hu, Chengfei Lyu, Zhihua Wu:
From Server-Based to Client-Based Machine Learning: A Comprehensive Survey. ACM Comput. Surv. 54(1): 6:1-6:36 (2022) - Jourik Ciesielski, Heidi Van Hiel:
Connecting client infrastructure with Yamagata Europe machine translation using JSON-based data exchange. EAMT 2022: 331-332 - Ilze Andersone, Agris Nikitenko, Valdis Bergs, Uldis Jansons:
Client Segmentation of Mobile Payment Parking Data Using Machine Learning. AIAI (2) 2022: 450-459 - 2021
- Mohamed Chiny, Omar Bencharef, Moulay Youssef Hadi, Younes Chihab:
A Client-Centric Evaluation System to Evaluate Guest's Satisfaction on Airbnb Using Machine Learning and NLP. Appl. Comput. Intell. Soft Comput. 2021: 6675790:1-6675790:14 (2021) - Thiago de Oliveira Lima, Methanias Colaço Júnior, Kleber H. de J. Prado, Israel Dias de J., Frederico Resende de Oliveira:
A Big Data Experiment to Evaluate the Effectiveness of Traditional Machine Learning Techniques Against LSTM Neural Networks in the Hotels Clients Opinion Mining. IEEE BigData 2021: 5199-5208 - Saki Takano, Akihiro Nakao, Saneyasu Yamaguchi, Masato Oguchi:
Facial Image Recognition in Distributed Machine Learning Using Rich Clients. GCCE 2021: 919-920 - Artem Los:
Storing data that is updated regularly on a client machine securely. IACR Cryptol. ePrint Arch. 2021: 937 (2021) - 2020
- Kareem Abdullah, Sara A. Attalla, Yasser Gadallah, Ayman Elezabi, Karim G. Seddik, Ayman Gaber, Dina Samak:
A Machine Learning-Based Technique for the Classification of Indoor/Outdoor Cellular Network Clients. CCNC 2020: 1-2 - 2019
- Mikhail Y. Kovalyov, Dominik Kress, Sebastian Meiswinkel, Erwin Pesch:
A parallel machine schedule updating game with compensations and clients averse to uncertain loss. Comput. Oper. Res. 103: 148-157 (2019) - Saurabh Dey, Qiang Ye, Srinivas Sampalli:
A machine learning based intrusion detection scheme for data fusion in mobile clouds involving heterogeneous client networks. Inf. Fusion 49: 205-215 (2019) - Edgar Gonzalo Cossio Franco, Jorge Alberto Delgado Cazarez, Daniel Noel Torres Godoy:
Predictive Model as a Tool for Acquiring a Certification for Client Companies and Certifying Entities with Machine Learning. Res. Comput. Sci. 148(6): 217-228 (2019) - Hiroki Kawakami, Satoshi Yamane:
Generalize IoT Device's Client Application with Virtual Machine. GCCE 2019: 992-995 - Dávid Ács, Adrian Colesa:
Securely Exposing Machine Learning Models to Web Clients using Intel SGX. ICCP 2019: 161-168 - Ch. Nanda Krishna, K. F. Bharati:
A Novel Chaotic based Privacy preserving machine learning model on large distributed client applications. ICDSE 2019: 144-148 - Ricardo Filipe, Filipe Araújo:
Client-Side Monitoring of HTTP Clusters Using Machine Learning Techniques. ICMLA 2019: 282-286 - Michal Zygmunt, Marek Konieczny, Slawomir Zielinski:
Accuracy of statistical machine learning methods in identifying client behavior patterns at network edge. TSP 2019: 575-579 - 2018
- Irina Poltavchenko:
De l'analyse d'opinions à la détection des problèmes d'interactions humain-machine: application à la gestion de la relation client. (Analysis of the detection of the human-machine interaction problems: application to the management of the customer relationship). Télécom Paris, France, 2018 - Ankit Kumar Jain, Brij B. Gupta:
Towards detection of phishing websites on client-side using machine learning based approach. Telecommun. Syst. 68(4): 687-700 (2018) - Sandra Lagén, Antonio Pascual-Iserte, Olga Muñoz, Josep Vidal:
Energy Efficiency in Latency-Constrained Application Offloading From Mobile Clients to Multiple Virtual Machines. IEEE Trans. Signal Process. 66(4): 1065-1079 (2018) - Mohammad Shariati, Ali Dehghantanha, Ben Martini, Kim-Kwang Raymond Choo:
Ubuntu One Investigation: Detecting Evidences on Client Machines. CoRR abs/1807.10448 (2018) - 2017
- Robert Falkenberg, Karsten Heimann, Christian Wietfeld:
Discover Your Competition in LTE: Client-Based Passive Data Rate Prediction by Machine Learning. GLOBECOM 2017: 1-7 - Petrônio Bezerra, Gustavo Martins, Reinaldo Gomes, Fellype Cavalcante, Anderson F. B. F. da Costa:
Evaluating live virtual machine migration overhead on client's application perspective. ICOIN 2017: 503-508
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