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Strongly convex functions
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Part 2 of book "Introduction to machine learning" provide with knowledge about: optimization; unconstrained smooth convex minimization; online learning and boosting; conditional densities; kernels and function spaces; linear models;...
136p
britaikridanik
05-07-2022
32
4
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In this paper we study the second order linear strong differential subordinations. Our results may be applied to deduce sufficient conditions for univalence in the unit disc, such as starlikeness, convexity, alpha-convexity, close-to-convexity respectively.
8p
tuongvidanh
06-01-2019
16
1
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In this paper, we consider a mathematical programming with equilibrium constraints (MPEC) where the objective and constraint functions are continuously differentiable. We establish the sufficient optimality condition for strict local minima of order m under the assumptions of generalized strong convexity of order m.
10p
vinguyentuongdanh
19-12-2018
33
1
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In this paper, we consider a nonsmooth semi-infinite multiobjective programming problem involving support functions. We establish sufficient optimality conditions for the primal problem. We formulate Mond-Weir type dual for the primal problem and establish weak, strong and strict converse duality theorems under various generalized convexity assumptions. Moreover, some special cases of our problem and results are presented.
14p
danhnguyentuongvi27
19-12-2018
20
1
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In this paper, we define some new generalizations of strongly convex functions of order m for locally Lipschitz functions using Clarke subdifferential. Suitable examples illustrating the non emptiness of the newly defined classes of functions and their relationships with classical notions of pseudoconvexity and quasiconvexity are provided.
16p
danhnguyentuongvi27
19-12-2018
37
1
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