Work

Deep Learning In Borel Measure

Year: 2025
Type: article
Abstract: Deep learning has had a profound impact on computer science in recent years, with applications to image recognition, language processing, bioinformatics, and more. Recently, Cohen et al. provided theoretical evidence for the superiority of deep learning over shallow learning. We formalized their mathematical proof using Isabelle/HOL. The Isabelle development simplifies and generalizes the original proof, while working around the limitations of the HOL type system. To support the formalization, we developed reusable libraries of formalized mathematics, including results about the matrix rank, the Borel measure, and multivariate polynomials as well as a library for tensor analysis.
Authors: Sakina Rizvi, Dr. Chitra Singh
Institution: AISECT University
Language: English
Open Access status: diamond
OpenAlex ID: W4412870921
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