all AI news
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. (arXiv:2205.01940v1 [cs.LG])
Web: http://arxiv.org/abs/2205.01940
May 5, 2022, 1:12 a.m. | Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
cs.LG updates on arXiv.org arxiv.org
This paper aims to theoretically analyze the complexity of feature
transformations encoded in DNNs with ReLU layers. We propose metrics to measure
three types of complexities of transformations based on the information theory.
We further discover and prove the strong correlation between the complexity and
the disentanglement of transformations. Based on the proposed metrics, we
analyze two typical phenomena of the change of the transformation complexity
during the training process, and explore the ceiling of a DNN's complexity. The
proposed …
More from arxiv.org / cs.LG updates on arXiv.org
Latest AI/ML/Big Data Jobs
Director, Applied Mathematics & Computational Research Division
@ Lawrence Berkeley National Lab | Berkeley, Ca
Business Data Analyst
@ MainStreet Family Care | Birmingham, AL
Assistant/Associate Professor of the Practice in Business Analytics
@ Georgetown University McDonough School of Business | Washington DC
Senior Data Science Writer
@ NannyML | Remote
Director of AI/ML Engineering
@ Armis Industries | Remote (US only), St. Louis, California
Digital Analytics Manager
@ Patagonia | Ventura, California