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Learning lipschitz functions

International Journal of Computer Mathematics, 1995
Considered here is the problem of learning a nonlinear mapping with uncountable domain and range. The learning model used is that of piecewise linear interpolation on random samples from the domain. More specifically, a network learns a function by approximating its value, typically within some small ∈, when presented an arbitrary element of the domain.
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Lipschitz pre-orders and Lipschitz utility functions

Russian Mathematical Surveys, 1984
The notion of the Lipschitz preorder as a preference ordering relation on a separable metric space is introduced, and it is shown that it leads to a Lipschitz utility function.
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Optimization of lipschitz continuous functions

Mathematical Programming, 1977
This paper contains basic results that are useful for building algorithms for the optimization of Lipschitz continuous functionsf on compact subsets of En. In this settingf is differentiable a.e. The theory involves a set-valued mappingxźźźf(x) whose range is the convex hull of existing values of źf and limits of źf on a closedź-ball,B(x, ź).
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SYMMETRIC LIPSCHITZ FUNCTIONS

We investigate Lipschitz symmetric functions on a Banach space  with a symmetric basis. We consider power symmetric polynomials on or  and show that they are Lipschitz on the unbounded subset of consisting of vectors on or  such that .
Danyliv I., Martsinkiv M.
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Lipschitz Functions

2019
Ştefan Cobzaş   +2 more
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Extreme Lipschitz functions

Mathematische Annalen, 1970
Rao, N. V., Roy, A. K.
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Lipschitz functions II

2022
Antonio José Guirao   +2 more
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Extension of lipschitz functions

Mathematical Notes of the Academy of Sciences of the USSR, 1980
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On the differentiability of Lipschitz functions with respect to measures in the Euclidean space

Geometric and Functional Analysis, 2016
Giovanni Alberti, Andrea Marchese
exaly  

Extensions of Lipschitz Functions

Journal of the London Mathematical Society, 1974
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