TY - GEN
T1 - Beyond L1
T2 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022
AU - Bertrand, Quentin
AU - Klopfenstein, Quentin
AU - Bannier, Pierre Antoine
AU - Gidel, Gauthier
AU - Massias, Mathurin
N1 - Publisher Copyright:
© 2022 Neural information processing systems foundation. All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - We propose a new fast algorithm to estimate any sparse generalized linear model with convex or non-convex separable penalties. Our algorithm is able to solve problems with millions of samples and features in seconds, by relying on coordinate descent, working sets and Anderson acceleration. It handles previously unaddressed models, and is extensively shown to improve state-of-art algorithms. We release skglm, a flexible, scikit-learn compatible package, which easily handles customized datafits and penalties.
AB - We propose a new fast algorithm to estimate any sparse generalized linear model with convex or non-convex separable penalties. Our algorithm is able to solve problems with millions of samples and features in seconds, by relying on coordinate descent, working sets and Anderson acceleration. It handles previously unaddressed models, and is extensively shown to improve state-of-art algorithms. We release skglm, a flexible, scikit-learn compatible package, which easily handles customized datafits and penalties.
UR - https://www.scopus.com/pages/publications/85163146227
M3 - Conference contribution
AN - SCOPUS:85163146227
T3 - Advances in Neural Information Processing Systems
BT - Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022
A2 - Koyejo, S.
A2 - Mohamed, S.
A2 - Agarwal, A.
A2 - Belgrave, D.
A2 - Cho, K.
A2 - Oh, A.
PB - Neural information processing systems foundation
Y2 - 28 November 2022 through 9 December 2022
ER -