A Survey on Transferability of Adversarial Examples across Deep Neural Networksarxiv.org/abs/2310.17626 摘要 深度神经网络(DNN)的出现彻底改变了各个领域,使图像识别、自然语言处理和科学问题解决等复杂任务的解决成为可能。然而,这一进展也暴露了一个令人担忧的脆弱性:对抗性示例。这些精心制作的输入,人类无法...
Wu, and X. Yi, “A survey of safety and trustworthiness ofdeep neural networks: Verification, testing, adversarial attack anddefence, and interpretability,” Computer Science Review, 2020. 5 [66] A. Geiger, P. Lenz, and R. Urtasun, “Are we ready for autonomousdriving? the kitti vision b...
Within artificial intelligence, Machine Learning and its subset Deep Learning (DL) have brought a paradigm shift with their computation power. Currently, DL is a widely used computational approach in machine learning. The uniqueness of deep learning is its capability to learn a large amount of ...
White, Paul Thomas, Bhaskar Mitra, Shawon Sarkar, Nicholas J. Belkin Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI 2021 paper bib He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine Interpretability and Analysis of Models for NLP A Primer in BERTology: ...
如果是想要压缩预训练模型(pre-trained deep nets)的话可以使用剪枝、权值共享或者低秩分解。如果需要端到端(end-end)的解决方案的话使用低秩分解和转移卷积滤波器的方法 对于某些特定领域的应用,具有人类先验知识的支撑。使用一些转移卷积滤波器(transferred convolutional filter)和结构化矩阵(structural matrix)这些具有先...
A Survey of Neural Networks and Formal Languages. arXiv 2020 paper bib Joshua Ackerman, George Cybenko A Survey of the Usages of Deep Learning in Natural Language Processing. IEEE 2018 paper bib Daniel W. Otter, Julian R. Medina, Jugal K. Kalita A Survey on Contextual Embeddings. arXiv 202...
Enhancing Accuracy with Recursive Feature Selection Using Multiple Machine Learning and Deep Learning Techniques on NSL-KDD Dataset Chapter © 2024 Performance and Complexity Tradeoffs of Feature Selection on Intrusion Detection System-Based Neural Network Classification with High-Dimensional Dataset Chapt...
Yu, “Recent advances in convolutional neural network acceleration,” Neurocomputing, vol. 323, pp. 37–51, 2019.[43] J. Bouvrie, “1 Introduction Notes on Convolutional Neural Networks,” 2006.[44] Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, no. 7553...
因为篇幅限制,在这篇文章中我们不会给出太多关于一般元学习技术详细的描述。关于元学习的一般概念,我们鼓励读者阅读先前的综述文章(Meta-learning for few-shot natural language processing: A survey;Meta-learning in neural networks:A survey; A survey of deep meta-learning)。
You can directly present a PR into this repo and we will record it for next version update of our survey. 🔥 New Next version of our survey is expected to update in: June 1, 2025. 🔥 We made our survey paper public and created this repository on December 28, 2024. Our grounding ...