Peter Ochs

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 37

Top Venues

CoRR

SIAM J. Optim.

J. Optim. Theory Appl.

SSVM

University of Freiburg, Germany (PHD)

Education History

University of Freiburg, Germany

PHD

Publications

Camille Castera, Peter Ochs
From Learning to Optimize to Learning Optimization Algorithms. CoRR (2024)
Camille Castera, Hédy Attouch, Jalal Fadili, Peter Ochs
Continuous Newton-like Methods Featuring Inertia and Variable Mass. SIAM J. Optim. 34 (1) (2024)
Michael Sucker, Jalal Fadili, Peter Ochs
Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation. CoRR (2024)
Shida Wang, Jalal Fadili, Peter Ochs
A Quasi-Newton Primal-Dual Algorithm with Line Search. SSVM (2023)
Silvia Bonettini, Peter Ochs, Marco Prato, Simone Rebegoldi
An abstract convergence framework with application to inertial inexact forward-backward methods. Comput. Optim. Appl. 84 (2) (2023)
Silvia Bonettini, Peter Ochs, Marco Prato, Simone Rebegoldi
An abstract convergence framework with application to inertial inexact forward-backward methods. CoRR (2023)
Severin Maier, Camille Castera, Peter Ochs
Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization. CoRR (2023)
Michael Sucker, Peter Ochs
PAC-Bayesian Learning of Optimization Algorithms. AISTATS (2023)
Mahesh Chandra Mukkamala, Jalal Fadili, Peter Ochs
Global convergence of model function based Bregman proximal minimization algorithms. J. Glob. Optim. 83 (4) (2022)
Sheheryar Mehmood, Peter Ochs
Fixed-Point Automatic Differentiation of Forward-Backward Splitting Algorithms for Partly Smooth Functions. CoRR (2022)
Michael Sucker, Peter Ochs
PAC-Bayesian Learning of Optimization Algorithms. CoRR (2022)
Sheheryar Mehmood, Peter Ochs
Differentiating the Value Function by using Convex Duality. AISTATS (2021)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. SSVM (2021)
Amirhossein Kardoost, Kalun Ho, Peter Ochs, Margret Keuper
Self-supervised Sparse to Dense Motion Segmentation. CoRR (2020)
Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, Shoham Sabach
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Nonconvex Optimization. SIAM J. Math. Data Sci. 2 (3) (2020)
Mahesh Chandra Mukkamala, Jalal Fadili, Peter Ochs
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms. CoRR (2020)
Emanuel Laude, Peter Ochs, Daniel Cremers
Bregman Proximal Mappings and Bregman-Moreau Envelopes Under Relative Prox-Regularity. J. Optim. Theory Appl. 184 (3) (2020)
Amirhossein Kardoost, Kalun Ho, Peter Ochs, Margret Keuper
Self-supervised Sparse to Dense Motion Segmentation. ACCV (2) (2020)
Sheheryar Mehmood, Peter Ochs
Automatic Differentiation of Some First-Order Methods in Parametric Optimization. AISTATS (2020)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Framework for Deep Linear Neural Networks. CoRR (2019)
Peter Ochs, Thomas Pock
Adaptive FISTA for Nonconvex Optimization. SIAM J. Optim. 29 (4) (2019)
Yura Malitsky, Peter Ochs
Model Function Based Conditional Gradient Method with Armijo-like Line Search. CoRR (2019)
Stephen Becker, Jalal Fadili, Peter Ochs
On Quasi-Newton Forward-Backward Splitting: Proximal Calculus and Convergence. SIAM J. Optim. 29 (4) (2019)
Peter Ochs
Unifying Abstract Inexact Convergence Theorems and Block Coordinate Variable Metric iPiano. SIAM J. Optim. 29 (1) (2019)
Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, Shoham Sabach
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization. CoRR (2019)
Peter Ochs, Yura Malitsky
Model Function Based Conditional Gradient Method with Armijo-like Line Search. ICML (2019)
Peter Ochs, Jalal Fadili, Thomas Brox
Non-smooth Non-convex Bregman Minimization: Unification and New Algorithms. J. Optim. Theory Appl. 181 (1) (2019)
Mahesh Chandra Mukkamala, Peter Ochs
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms. NeurIPS (2019)
Mahesh Chandra Mukkamala, Peter Ochs
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms. CoRR (2019)
Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller
Lifting Layers: Analysis and Applications. CoRR (2018)
Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller
Lifting Layers: Analysis and Applications. ECCV (1) (2018)
Jón Arnar Tómasson, Peter Ochs, Joachim Weickert
AFSI: Adaptive Restart for Fast Semi-Iterative Schemes for Convex Optimisation. GCPR (2018)
Peter Ochs
Local Convergence of the Heavy-Ball Method and iPiano for Non-convex Optimization. J. Optim. Theory Appl. 177 (1) (2018)
Peter Ochs, Jalal Fadili, Thomas Brox
Non-smooth Non-convex Bregman Minimization: Unification and new Algorithms. CoRR (2017)
Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock
Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems. J. Math. Imaging Vis. 56 (2) (2016)
Sabine Müller, Peter Ochs, Joachim Weickert, Norbert M. Graf
Robust Interactive Multi-label Segmentation with an Advanced Edge Detector. GCPR (2016)
David Hafner, Peter Ochs, Joachim Weickert, Martin Reißel, Sven Grewenig
FSI Schemes: Fast Semi-Iterative Solvers for PDEs and Optimisation Methods. GCPR (2016)
Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock
Bilevel Optimization with Nonsmooth Lower Level Problems. SSVM (2015)
Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock
On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision. SIAM J. Imaging Sci. 8 (1) (2015)
Peter Ochs, Thomas Brox, Thomas Pock
iPiasco: Inertial Proximal Algorithm for Strongly Convex Optimization. J. Math. Imaging Vis. 53 (2) (2015)
Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock
iPiano: Inertial Proximal Algorithm for Nonconvex Optimization. SIAM J. Imaging Sci. 7 (2) (2014)
Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock
iPiano: Inertial Proximal Algorithm for Non-Convex Optimization. CoRR (2014)
Peter Ochs, Jitendra Malik, Thomas Brox
Segmentation of Moving Objects by Long Term Video Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 36 (6) (2014)
Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock
An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision. CVPR (2013)
Maja Temerinac-Ott, Olaf Ronneberger, Peter Ochs, Wolfgang Driever, Thomas Brox, Hans Burkhardt
Multiview Deblurring for 3-D Images from Light-Sheet-Based Fluorescence Microscopy. IEEE Trans. Image Process. 21 (4) (2012)
Peter Ochs, Thomas Brox
Higher order motion models and spectral clustering. CVPR (2012)
Naveen Shankar Nagaraja, Peter Ochs, Kun Liu, Thomas Brox
Hierarchy of Localized Random Forests for Video Annotation. DAGM/OAGM Symposium (2012)
Peter Ochs, Thomas Brox
Object segmentation in video: A hierarchical variational approach for turning point trajectories into dense regions. ICCV (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Peter Ochs