Emanuel Laude

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 17

Top Topics

Convex Relaxation

Markov Random Field

Transductive Inference

Bundle Adjustment

Top Venues

Publications

Konstantinos A. Oikonomidis, Emanuel Laude, Puya Latafat, Andreas Themelis, Panagiotis Patrinos
Adaptive proximal gradient methods are universal without approximation. CoRR (2024)
Emanuel Laude, Andreas Themelis, Panagiotis Patrinos
Dualities for Non-Euclidean Smoothness and Strong Convexity under the Light of Generalized Conjugacy. SIAM J. Optim. 33 (4) (2023)
Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM J. Imaging Sci. 15 (3) (2022)
Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. CoRR (2021)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. SSVM (2021)
Emanuel Laude, Peter Ochs, Daniel Cremers
Bregman Proximal Mappings and Bregman-Moreau Envelopes Under Relative Prox-Regularity. J. Optim. Theory Appl. 184 (3) (2020)
Nikolaus Demmel, Maolin Gao, Emanuel Laude, Tao Wu, Daniel Cremers
Distributed Photometric Bundle Adjustment. 3DV (2020)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Framework for Deep Linear Neural Networks. CoRR (2019)
Emanuel Laude, Tao Wu, Daniel Cremers
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems. CoRR (2019)
Emanuel Laude, Tao Wu, Daniel Cremers
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems. AISTATS (2019)
Emanuel Laude, Tao Wu, Daniel Cremers
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization. AISTATS (2018)
Emanuel Laude, Jan-Hendrik Lange, Jonas Schüpfer, Csaba Domokos, Laura Leal-Taixé, Frank R. Schmidt, Bjoern Andres, Daniel Cremers
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs. CVPR (2018)
Emanuel Laude, Jan-Hendrik Lange, Frank R. Schmidt, Bjoern Andres, Daniel Cremers
Discrete-Continuous Splitting for Weakly Supervised Learning. CoRR (2017)
Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. CoRR (2016)
Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Relaxation of Nonconvex Energies. CVPR (2016)
Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. ECCV (1) (2016)
Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Relaxation of Nonconvex Energies. CoRR (2015)