High-order evaluation complexity for convexly-constrained optimization with non-Lipschitzian group sparsity terms
Author:
Funder
Hong Kong Research Grant Council
Publisher
Springer Science and Business Media LLC
Subject
General Mathematics,Software
Link
https://link.springer.com/content/pdf/10.1007/s10107-020-01470-9.pdf
Reference39 articles.
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2. Beck, A., Hallak, N.: Optimization problems involving group sparsity terms. Math. Program. 178, 39–67 (2019)
3. Baldassarre, L., Bhan, N., Cevher, V., Kyrillidis, A., Satpathi, S.: Group-sparse model selection: hardness and relaxations. IEEE Trans. Inf. Theory 62, 6508–6534 (2016)
4. Bellavia, S., Gurioli, G., Morini, B., Toint, PhL: Deterministic and stochastic inexact regularization algorithms for nonconvex optimization with optimal complexity. SIAM J. Optim. 29, 2881–2915 (2019)
5. Bian, W., Chen, X.: Worst-case complexity of smoothing quadratic regularization methods for non-Lipschitzian optimization. SIAM J. Optim. 23, 1718–1741 (2013)
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