Hochschulschrift

New convex relaxations and global optimality in variational imaging

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Dimensions: 30 cm

Extent: xxiii, 99 Seiten

Language: Englisch

Notes: Illustrationen, Diagramme
Heidelberg University, Dissertation, 2016

Classification: Mathematik
Informatik

Keyword: Bildverarbeitung
Maschinelles Sehen info
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Event: Veröffentlichung

(where): Heidelberg

(when): [2016]

Creator: Swoboda, Paul

Table of contents: https://d-nb.info/1141619644/04

Rights: Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.

Last update: 11.06.2025, 2:27 PM CEST

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Hochschulschrift

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Swoboda, Paul

Time of origin

[2016]

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Tight Convex Relaxations for the Expansion Planning Problem

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New convex relaxations and global optimality in variational imaging

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Other Objects (12)

New Convex Relaxations and Global Optimality in Variational Imaging

Convex Relaxations of Componentwise Convex Functions

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Convex Quadratic Programming Relaxations for Network Scheduling Problems

Convex quadratic and semidefinite programming relaxations in Scheduling

Tight Convex Relaxations for the Expansion Planning Problem

Solving Two-stage Quadratic Multiobjective Problems via Optimality and Relaxations

Strengthening convex relaxations of 0/1-sets using Boolean formulas

Using dual relaxations in multiobjective mixed-integer convex quadratic programming

Relaxations

Sufficient second-order optimality conditions for convex control constraints

Second-order cone AC optimal power flow: convex relaxations and feasible solutions

New Convex Relaxations and Global Optimality in Variational Imaging

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Convex relaxations for mixed-integer nonlinear programs

Convex Quadratic Programming Relaxations for Network Scheduling Problems

Convex quadratic and semidefinite programming relaxations in Scheduling

Tight Convex Relaxations for the Expansion Planning Problem

Solving Two-stage Quadratic Multiobjective Problems via Optimality and Relaxations

Strengthening convex relaxations of 0/1-sets using Boolean formulas

Using dual relaxations in multiobjective mixed-integer convex quadratic programming

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Sufficient second-order optimality conditions for convex control constraints

Second-order cone AC optimal power flow: convex relaxations and feasible solutions

New Convex Relaxations and Global Optimality in Variational Imaging

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Convex quadratic and semidefinite programming relaxations in Scheduling

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Using dual relaxations in multiobjective mixed-integer convex quadratic programming

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