A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training
Abstract Deep learning is one of the most popular machine learning methods, and has been used in many applications. However, conventional deep learning is a fully deterministic model that has difficulty reducing data uncertainty while shedding no light on model transparency. To this end, a novel adv...
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| Main Authors: | Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-025-01928-3 |
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