Emanuel Laude
Title
Cited by
Cited by
Year
Sublabel-accurate relaxation of nonconvex energies
T Mollenhoff, E Laude, M Moeller, J Lellmann, D Cremers
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
442016
Sublabel-accurate convex relaxation of vectorial multilabel energies
E Laude, T Möllenhoff, M Moeller, J Lellmann, D Cremers
European conference on computer vision, 614-627, 2016
222016
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs
E Laude, JH Lange, J Schüpfer, C Domokos, L Leal-Taixé, FR Schmidt, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
7*2018
Bregman proximal mappings and Bregman–Moreau envelopes under relative prox-regularity
E Laude, P Ochs, D Cremers
Journal of Optimization Theory and Applications 184 (3), 724-761, 2020
62020
A nonconvex proximal splitting algorithm under Moreau-Yosida regularization
E Laude, T Wu, D Cremers
International Conference on Artificial Intelligence and Statistics, 491-499, 2018
62018
Optimization of inf-convolution regularized nonconvex composite problems
E Laude, T Wu, D Cremers
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
42019
Bregman proximal framework for deep linear neural networks
MC Mukkamala, F Westerkamp, E Laude, D Cremers, P Ochs
arXiv preprint arXiv:1910.03638, 2019
32019
Lifting the convex conjugate in lagrangian relaxations: A tractable approach for continuous Markov random fields
H Bauermeister, E Laude, T Möllenhoff, M Moeller, D Cremers
arXiv preprint arXiv:2107.06028, 2021
12021
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization.
MC Mukkamala, F Westerkamp, E Laude, D Cremers, P Ochs
SSVM, 204-215, 2021
2021
Distributed Photometric Bundle Adjustment
N Demmel, M Gao, E Laude, T Wu, D Cremers
2020 International Conference on 3D Vision (3DV), 140-149, 2020
2020
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs–Supplementary Material–
E Laude, JH Lange, J Schüpfer, C Domokos, L Leal-Taixé, FR Schmidt, ...
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