ML for Design QoR Prediction-Reference-Cited by-同舟云学术

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ML for Design QoR Prediction

Published:2022 Issue: Volume: Page:3-33
ISSN:
Container-title:Machine Learning Applications in Electronic Design Automation
language:
Short-container-title:

Author:

Kahng Andrew B.,Wang Zhiang

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-13074-8_1

Reference51 articles.

1. Agnesina, A., Chang, K., Lim, S.K.: VLSI placement parameter optimization using deep reinforcement learning. In: Proceedings of the IEEE/ACM International Conference on Computer Aided Design (ICCAD), pp. 1–9 (2020)

2. Agnesina, A., Pentapati, S., Lim, S.K.: A general framework for VLSI tool parameter optimization with deep reinforcement learning. In: Proceedings of the International Conference on Neural Information Processing Systems (NeurIPS) (2021)

3. Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization (2016).Preprint. arXiv:1607.06450

4. Barboza, E.C., Shukla, N., Chen, Y., Hu, J.: Machine learning-based pre-routing timing prediction with reduced pessimism. In: Proceedings of the ACM/IEEE Design Automation Conference (DAC), pp. 1–6 (2019)

5. Breiman, L.: Random forests. In: Machine Learning, pp. 5–32 (2001)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Solvers, Engines, Tools and Flows: The Next Wave for AI/ML in Physical Design;Proceedings of the 2024 International Symposium on Physical Design;2024-03-12

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