MONOTONICITY FOR MULTIOBJECTIVE ACCELERATED PROXIMAL GRADIENT METHODS
Author:
Affiliation:
1. Kyoto University
Publisher
The Operations Research Society of Japan
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://www.jstage.jst.go.jp/article/jorsj/67/1/67_1/_pdf
Reference24 articles.
1. [1] A. Beck and M. Teboulle: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM Journal on Imaging Sciences, 2 (2009), 183–202.
2. [2] A. Beck and M. Teboulle: Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. IEEE Transactions on Image Processing, 18 (2009), 2419–2434.
3. [3] D.P. Bertsekas: Nonlinear Programming (2nd ed., Athena Scientific, 1999).
4. [4] M. Binder, J. Moosbauer, J. Thomas and B. Bischl: Multi-objective hyperparameter tuning and feature selection using filter ensembles. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (Association for Computing Machinery, 2020), 471–479.
5. [5] H. Bonnel, A.N. Iusem, and B.F. Svaiter: Proximal methods in vector optimization. SIAM Journal on Optimization, 15 (2005), 953–970.
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