Bibliography on non-differentiable optimization and non-smooth analysis

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Adversarial Variational Optimization of Non-Differentiable Simulators

Complex computer simulators are increasingly used across fields of science as generative models tying parameters of an underlying theory to experimental observations. Inference in this setup is often difficult, as simulators rarely admit a tractable density or likelihood function. We introduce Adversarial Variational Optimization (AVO), a likelihood-free inference algorithm for fitting a non-di...

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Non-differentiable Optimization of Fuzzy Logic Systems

In the present use of fuzzy logic systems tuning of their parameters has become an important issue. Many techniques, mainly based on the application of gradient descent, have been applied to this task generally in order to minimize a quadratic error function. The class of fuzzy logic systems using piecewise linear membership functions (e.g., triangular or trapezoidal) and/or minimum or maximum ...

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Semi-smooth Newton Methods for Non-differentiable Optimization Problems Lipschitz Lectures

2 These notes constitute no original research work. Rather they draw from the results with collaborators that are quoted in the reference section.

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Mangasarian-Fromovitz and Zangwill Conditions For Non-Smooth Infinite Optimization problems in Banach Spaces

In this paper we study optimization problems with infinite many inequality constraints on a Banach space where the objective function and the binding constraints are Lipschitz near the optimal solution. Necessary optimality conditions and constraint qualifications in terms of Michel-Penot subdifferential are given.

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ژورنال

عنوان ژورنال: Journal of Computational and Applied Mathematics

سال: 1981

ISSN: 0377-0427

DOI: 10.1016/0771-050x(81)90056-5