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The paper proposes and develops a novel inexact gradient method (IGD) for minimizing C1-smooth functions with Lipschitzian gradients, i.e., for problems of C1,1 optimization.
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L. Bottou, F. E. Curtis and J. Nocedal, Optimization methods for large-scale machine learning, SIAM Rev
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A. Themelis, B. Hermans and P. Patrinos, A new envelope function for nonsmooth DC optimization, Proc. 59th IEEE Conf. Dec. Control
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A. S. Berahas, L. Cao and K. Scheinberg, Global convergence rate analysis of a generic linesearch algorithm with noise, SIAM J. Optim
2021
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A. S. Berahas, L. Cao, K. Choromanski and K. Scheinberg, A theoretical and empirical comparison of gradient approximations in derivative-free optimization, Found. Comput. Math
2022
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B. S. Mordukhovich and N. M. Nam, Convex Analysis and Beyond, I: Basic Theory
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2023
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2024
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