We stand with Ukraine

We stand with Ukraine

Peter Ochs

Orcid: 0000-0002-4880-7511

Affiliations:

Saarland University, Department of Mathematics, Germany
University of Freiburg, Department of Computer Science, Germany

According to our database¹, Peter Ochs authored at least 44 papers between 2011 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

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Links

Online presence:

On csauthors.net:

Bibliography

2024

Continuous Newton-like Methods Featuring Inertia and Variable Mass.

[BibT_eX]

[DOI]

Camille Castera

,

,

,

SIAM J. Optim., March, 2024

Automatic Differentiation of Optimization Algorithms with Time-Varying Updates.

[BibT_eX]

[DOI]

Sheheryar Mehmood

,

CoRR, 2024

A Generalization Result for Convergence in Learning-to-Optimize.

[BibT_eX]

[DOI]

,

CoRR, 2024

A Markovian Model for Learning-to-Optimize.

[BibT_eX]

[DOI]

,

CoRR, 2024

From Learning to Optimize to Learning Optimization Algorithms.

[BibT_eX]

[DOI]

Camille Castera

,

CoRR, 2024

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation.

[BibT_eX]

[DOI]

,

,

CoRR, 2024

2023

An abstract convergence framework with application to inertial inexact forward-backward methods.

[BibT_eX]

[DOI]

Silvia Bonettini

,

,

,

Simone Rebegoldi

Comput. Optim. Appl., March, 2023

Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization.

[BibT_eX]

[DOI]

,

Camille Castera

,

CoRR, 2023

A Quasi-Newton Primal-Dual Algorithm with Line Search.

[BibT_eX]

[DOI]

,

,

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

PAC-Bayesian Learning of Optimization Algorithms.

[BibT_eX]

[DOI]

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Global convergence of model function based Bregman proximal minimization algorithms.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

,

J. Glob. Optim., 2022

Fixed-Point Automatic Differentiation of Forward-Backward Splitting Algorithms for Partly Smooth Functions.

[BibT_eX]

[DOI]

Sheheryar Mehmood

,

CoRR, 2022

2021

Bregman Proximal Gradient Algorithms for Deep Matrix Factorization.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

Felix Westerkamp

,

,

,

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

Differentiating the Value Function by using Convex Duality.

[BibT_eX]

[DOI]

Sheheryar Mehmood

,

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Nonconvex Optimization.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

,

,

SIAM J. Math. Data Sci., 2020

Bregman Proximal Mappings and Bregman-Moreau Envelopes Under Relative Prox-Regularity.

[BibT_eX]

[DOI]

,

,

J. Optim. Theory Appl., 2020

Automatic Differentiation of Some First-Order Methods in Parametric Optimization.

[BibT_eX]

[DOI]

Sheheryar Mehmood

,

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Self-supervised Sparse to Dense Motion Segmentation.

[BibT_eX]

[DOI]

Amirhossein Kardoost

,

,

,

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

Adaptive FISTA for Nonconvex Optimization.

[BibT_eX]

[DOI]

,

SIAM J. Optim., 2019

Unifying Abstract Inexact Convergence Theorems and Block Coordinate Variable Metric iPiano.

[BibT_eX]

[DOI]

SIAM J. Optim., 2019

On Quasi-Newton Forward-Backward Splitting: Proximal Calculus and Convergence.

[BibT_eX]

[DOI]

,

,

SIAM J. Optim., 2019

Non-smooth Non-convex Bregman Minimization: Unification and New Algorithms.

[BibT_eX]

[DOI]

,

,

J. Optim. Theory Appl., 2019

Bregman Proximal Framework for Deep Linear Neural Networks.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

Felix Westerkamp

,

,

,

CoRR, 2019

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

,

,

CoRR, 2019

Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

,

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Model Function Based Conditional Gradient Method with Armijo-like Line Search.

[BibT_eX]

[DOI]

,

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Local Convergence of the Heavy-Ball Method and iPiano for Non-convex Optimization.

[BibT_eX]

[DOI]

J. Optim. Theory Appl., 2018

Lifting Layers: Analysis and Applications.

[BibT_eX]

[DOI]

,

,

Laura Leal-Taixé

,

Michael Möller

Proceedings of the Computer Vision - ECCV 2018, 2018

AFSI: Adaptive Restart for Fast Semi-Iterative Schemes for Convex Optimisation.

[BibT_eX]

[DOI]

Jón Arnar Tómasson

,

,

Joachim Weickert

Proceedings of the Pattern Recognition - 40th German Conference, 2018

2016

Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems.

[BibT_eX]

[DOI]

,

,

,

J. Math. Imaging Vis., 2016

Robust Interactive Multi-label Segmentation with an Advanced Edge Detector.

[BibT_eX]

[DOI]

,

,

Joachim Weickert

,

Norbert M. Graf

Proceedings of the Pattern Recognition - 38th German Conference, 2016

FSI Schemes: Fast Semi-Iterative Solvers for PDEs and Optimisation Methods.

[BibT_eX]

[DOI]

,

,

Joachim Weickert

,

,

Proceedings of the Pattern Recognition - 38th German Conference, 2016

2015

Long term motion analysis for object level grouping and nonsmooth optimization methods = Langzeitanalyse von Bewegungen zur objektorientierten Gruppierung und nichglatte Optimierungsmethoden.

[BibT_eX]

[DOI]

PhD thesis, 2015

On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision.

[BibT_eX]

[DOI]

,

Alexey Dosovitskiy

,

,

SIAM J. Imaging Sci., 2015

iPiasco: Inertial Proximal Algorithm for Strongly Convex Optimization.

[BibT_eX]

[DOI]

,

,

J. Math. Imaging Vis., 2015

Bilevel Optimization with Nonsmooth Lower Level Problems.

[BibT_eX]

[DOI]

,

,

,

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

2014

iPiano: Inertial Proximal Algorithm for Nonconvex Optimization.

[BibT_eX]

[DOI]

,

,

,

SIAM J. Imaging Sci., 2014

Segmentation of Moving Objects by Long Term Video Analysis.

[BibT_eX]

[DOI]

,

,

IEEE Trans. Pattern Anal. Mach. Intell., 2014

iPiano: Inertial Proximal Algorithm for Non-Convex Optimization.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2014

2013

An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision.

[BibT_eX]

[DOI]

,

Alexey Dosovitskiy

,

,

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

Multiview Deblurring for 3-D Images from Light-Sheet-Based Fluorescence Microscopy.

[BibT_eX]

[DOI]

Maja Temerinac-Ott

,

Olaf Ronneberger

,

,

Wolfgang Driever

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,

IEEE Trans. Image Process., 2012

Hierarchy of Localized Random Forests for Video Annotation.

[BibT_eX]

[DOI]

Naveen Shankar Nagaraja

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,

,

Proceedings of the Pattern Recognition, 2012

Higher order motion models and spectral clustering.

[BibT_eX]

[DOI]

,

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Object segmentation in video: A hierarchical variational approach for turning point trajectories into dense regions.

[BibT_eX]

[DOI]

,

Proceedings of the IEEE International Conference on Computer Vision, 2011

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