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Dependence of Computational Models on Input Dimension: Tractability of Approximation and Optimization Tasks., , and . IEEE Trans. Inf. Theory, 58 (2): 1203-1214 (2012)On a Variational Norm Tailored to Variable-Basis Approximation Schemes., and . IEEE Trans. Inf. Theory, 57 (1): 549-558 (2011)Algorithm of Incremental Approximation Using Variation of a Function with Respect to a Subset., and . NC, page 896-899. ICSC Academic Press, International Computer Science Conventions, Canada / Switzerland, (1998)Suboptimal Solutions to Team Optimization Problems with Stochastic Information Structure., , and . SIAM J. Optimization, 22 (1): 212-243 (2012)Special Issue Optimization for Machine Learning Guest Editorial., and . Soft Comput., 25 (19): 12565-12567 (2021)Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets., and . Discret. Appl. Math., 155 (15): 1930-1942 (2007)Tight Bounds on Rates of Neural-Network Approximation., and . ICANN, volume 2130 of Lecture Notes in Computer Science, page 277-284. Springer, (2001)On Tractability of Neural-Network Approximation., , and . ICANNGA, volume 5495 of Lecture Notes in Computer Science, page 11-21. Springer, (2009)Can dictionary-based computational models outperform the best linear ones?, , and . Neural Networks, 24 (8): 881-887 (2011)Some comparisons of complexity in dictionary-based and linear computational models., , and . Neural Networks, 24 (2): 171-182 (2011)