23 citations to https://www.mathnet.ru/rus/conap1
  1. Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta, “Scalable Frank–Wolfe on Generalized Self-Concordant Functions via Simple Steps”, SIAM J. Optim., 34:3 (2024), 2231  crossref
  2. Troubleshooting for Network Operators, 2023, 141  crossref
  3. A. V. Dereventsov, V. N. Temlyakov, “Biorthogonal Greedy Algorithms in convex optimization”, Appl. Comput. Harmon. Anal., 60 (2022), 489–511  mathnet  crossref
  4. Ching-Kang Ing, Chin-Yi Lin, Po-Hsiang Peng, Yu-Ming Hsieh, Fan-Tien Cheng, “Golden Path Search Algorithm for the KSA Scheme”, IEEE Trans. Automat. Sci. Eng., 19:3 (2022), 1517  crossref
  5. Wenhui Zhang, Peixin Ye, Shuo Xing, Xu Xu, “Optimality of the Approximation and Learning by the Rescaled Pure Super Greedy Algorithms”, Axioms, 11:9 (2022), 437  crossref
  6. Van Tong, Sami Souihi, Hai Anh Tran, Abdelhamid Mellouk, “SDN-Based Application-Aware Segment Routing for Large-Scale Network”, IEEE Systems Journal, 16:3 (2022), 4401  crossref
  7. Alexander J. Zaslavski, SpringerBriefs in Optimization, Optimization in Banach Spaces, 2022, 1  crossref
  8. Shao-Bo Lin, Shaojie Tang, Yao Wang, Di Wang, “Toward Efficient Ensemble Learning with Structure Constraints: Convergent Algorithms and Applications”, INFORMS Journal on Computing, 34:6 (2022), 3096  crossref
  9. Lin Xu, Xiangyong Cao, Jing Yao, Zheng Yan, “Orthogonal Super Greedy Learning for Sparse Feedforward Neural Networks”, IEEE Trans. Netw. Sci. Eng., 9:1 (2022), 161  crossref
  10. Sergei Sidorov, Kirill Spiridinov, Lecture Notes in Computer Science, 12755, Mathematical Optimization Theory and Operations Research, 2021, 192  crossref
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