A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning.

Yaqing Wang|Quanming Yao|James T. Kwok


Anthology ID:DBLP:conf/www/WangYK21
Volume:WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021.
Year:2021
Venue:The Web Conference (WWW)
Publisher:ACM / IW3C2
Pages:1798-1808
URL:https://doi.org/10.1145/3442381.3450142
DOI:https://doi.org/10.1145/3442381.3450142
DBLP:conf/www/WangYK21
BibTeX:
@inproceedings{wang-2021-scalable, author = {Yaqing Wang and Quanming Yao and James T. Kwok}, editor = {Jure Leskovec and Marko Grobelnik and Marc Najork and Jie Tang and Leila Zia}, title = {{A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning}}, booktitle = {{WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021}}, pages = {1798--1808}, publisher = {ACM / IW3C2}, year = {2021}, url = {https://doi.org/10.1145/3442381.3450142}, doi = {https://doi.org/10.1145/3442381.3450142} }