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Mathematical Challenges in Deep Learning

Authors :
Nia, Vahid Partovi
Zhang, Guojun
Kobyzev, Ivan
Metel, Michael R.
Li, Xinlin
Sun, Ke
Hemati, Sobhan
Asgharian, Masoud
Kong, Linglong
Liu, Wulong
Chen, Boxing
Publication Year :
2023

Abstract

Deep models are dominating the artificial intelligence (AI) industry since the ImageNet challenge in 2012. The size of deep models is increasing ever since, which brings new challenges to this field with applications in cell phones, personal computers, autonomous cars, and wireless base stations. Here we list a set of problems, ranging from training, inference, generalization bound, and optimization with some formalism to communicate these challenges with mathematicians, statisticians, and theoretical computer scientists. This is a subjective view of the research questions in deep learning that benefits the tech industry in long run.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2303.15464
Document Type :
Working Paper