Semantic Scholar Open Access 2021 380 sitasi

Model complexity of deep learning: a survey

Xia Hu Lingyang Chu J. Pei Weiqing Liu Jiang Bian

Abstrak

Model complexity is a fundamental problem in deep learning. In this paper, we conduct a systematic overview of the latest studies on model complexity in deep learning. Model complexity of deep learning can be categorized into expressive capacity and effective model complexity. We review the existing studies on those two categories along four important factors, including model framework, model size, optimization process, and data complexity. We also discuss the applications of deep learning model complexity including understanding model generalization, model optimization, and model selection and design. We conclude by proposing several interesting future directions.

Topik & Kata Kunci

Computer Science

Penulis (5)

Xia Hu

Lingyang Chu

J. Pei

Weiqing Liu

Jiang Bian

Format Sitasi

APA MLA BibTeX

Hu, X., Chu, L., Pei, J., Liu, W., Bian, J. (2021). Model complexity of deep learning: a survey. https://doi.org/10.1007/s10115-021-01605-0

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Total Sitasi: 380×
Sumber Database: Semantic Scholar
DOI: 10.1007/s10115-021-01605-0
Akses: Open Access ✓