Training Support Vector Machines for Dealing with the ImageNet Challenging Problem-Reference-Cited by-同舟云学术

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Training Support Vector Machines for Dealing with the ImageNet Challenging Problem

Published:2021-12-08 Issue: Volume: Page:235-246
ISSN:2367-3370
Container-title:Modelling, Computation and Optimization in Information Systems and Management Sciences
language:
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Author:

Do Thanh-Nghi,Le Thi Hoai An

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-92666-3_20

Reference33 articles.

1. Lecture Notes in Computer Science;A Bosch,2006

2. Bottou, L., Bousquet, O.: The tradeoffs of large scale learning. In: Platt, J., Koller, D., Singer, Y., Roweis, S. (eds.) Advances in Neural Information Processing Systems, vol. 20, pp. 161–168. NIPS Foundation (2008). http://books.nips.cc

3. Breiman, L.: Bagging predictors. Mach. Learn. 24(2), 123–140 (1996)

4. Chang, C.C., Lin, C.J.: LIBSVM : a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(27), 1–27 (2011)

5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);NV Chawla,2003

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1. Fuzzy Least Squares Support Vector Machine with Fuzzy Hyperplane;Neural Processing Letters;2023-04-13

2. ImageNet Challenging Classification with the Raspberry Pis: A Federated Learning Algorithm of Local Stochastic Gradient Descent Models;Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications;2022

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