Homotopy Methods for Linear Optimization Problems with Sparsity Penalty and Applications

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Alternative title: Homotopie-Methoden für Lineare Optimierungsprobleme mit L1-Strafterm und Anwendungen

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: Braunschweig, Technische Universität Braunschweig, Dissertation, 2018

Keyword: Houdini, Harry
Linear programming
Discriminant analysis

Event: Veröffentlichung

(where): Braunschweig

(who): Technische Universität Braunschweig

(when): 2018

Creator: Brauer, Christoph

Contributor: Lorenz, Dirk

DOI: 10.24355/dbbs.084-201804250929-0

URN: urn:nbn:de:gbv:084-2018042509304

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:57 AM CEST

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Brauer, Christoph
Lorenz, Dirk
Technische Universität Braunschweig

Time of origin

2018

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Homotopy Methods for Linear Optimization Problems with Sparsity Penalty and Applications

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Other Objects (12)

Computational approaches to non-convex, sparsity-inducing multi-penalty regularization

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Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program : NN2MILP

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Theoretical Aspects in Penalty Hyperparameters Optimization

Relative Cauchy Evolution for Linear Homotopy AQFTs

Nonlinear multiobjective optimization : a generalized homotopy approach

On nondegenerate M-stationary points for sparsity constrained nonlinear optimization

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Theoretical Aspects in Penalty Hyperparameters Optimization

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On nondegenerate M-stationary points for sparsity constrained nonlinear optimization

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Linear Yang–Mills Theory as a Homotopy AQFT

Predictive stability criteria for penalty selection in linear models

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Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program: NN2MILP

Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program : NN2MILP

A Unifying Framework for Sparsity-Constrained Optimization

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