adam-a-method-for-stochastic-optimization-2021-006

Diederik P. Kingma, Jimmy Ba

0 Est. reading time5 views0 downloads0 reviews

Verified repository recordMetadataMetadata 90%Repository readiness 92%

adam-a-method-for-stochastic-optimization-2021-006

Diederik P. Kingma, Jimmy BaUFTAN UNIVERSITYComputer Science2021

Abstract

This record links to the Adam optimization paper, which presents an adaptive learning-rate method widely used in deep learning. It is a compact but realistic technical PDF for testing keyword relevance, citation generation, and external document access.

Metadata

Author: Diederik P. Kingma, Jimmy Ba
Supervisor: Dr. Theresa I. Ajayi
Faculty: Science
Department: Computer Science
Document type: Masters Thesis
Year: 2021
Keywords: Adam optimizer, stochastic optimization, adaptive learning rate, neural networks, gradient descent
Access: Metadata
License: all_rights_reserved

Cite this work

Auto-generated from the record metadata: authors, journal title, DOI, volume, issue/serial, pages and publication date. Review before final academic use.

Diederik P. Kingma, Jimmy Ba (2026). adam-a-method-for-stochastic-optimization-2021-006 [Masters Thesis]. UFTAN UNIVERSITY. https://inrepscholar.com/uftan-university/projects/945

Source fields used: Diederik P. Kingma, Jimmy Ba

Export citation and metadata

APA RIS BibTeX Dublin Core DataCite

Academic reviews

No approved reviews yetReviews and citation feedback appear here after moderation.

Sign in to submit a review or correction suggestion for this record.

adam-a-method-for-stochastic-optimization-2021-006

Abstract

Metadata

Cite this work

Academic reviews

Related records