23 citations to https://www.mathnet.ru/rus/conap1
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Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta, “Scalable Frank–Wolfe on Generalized Self-Concordant Functions via Simple Steps”, SIAM J. Optim., 34:3 (2024), 2231
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Troubleshooting for Network Operators, 2023, 141
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A. V. Dereventsov, V. N. Temlyakov, “Biorthogonal Greedy Algorithms in convex optimization”, Appl. Comput. Harmon. Anal., 60 (2022), 489–511
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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
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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
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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
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Alexander J. Zaslavski, SpringerBriefs in Optimization, Optimization in Banach Spaces, 2022, 1
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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
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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
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Sergei Sidorov, Kirill Spiridinov, Lecture Notes in Computer Science, 12755, Mathematical Optimization Theory and Operations Research, 2021, 192