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20112022
most citedFlowNet: Learning Optical Flow with Convolutional Networks

604 citations · 1.4k across the 64 of their papers we have counts for

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8 papers · 1 filter

math.OC20212 cited

Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation

Florian Bernard, Daniel Cremers, Johan Thunberg

We address the non-convex optimisation problem of finding a sparse matrix on the Stiefel manifold (matrices with mutually orthogonal columns of unit length) that maximises (or mini…

math.OC20201 cited

Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning

Zhenzhang Ye, Thomas Möllenhoff, Tao Wu +1

Structured convex optimization on weighted graphs finds numerous applications in machine learning and computer vision. In this work, we propose a novel adaptive preconditioning str…

math.OC20195 cited

Bregman Proximal Framework for Deep Linear Neural Networks

Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude +2

A typical assumption for the analysis of first order optimization methods is the Lipschitz continuity of the gradient of the objective function. However, for many practical applica…

math.OC2019

Bregman Proximal Mappings and Bregman-Moreau Envelopes under Relative Prox-Regularity

Emanuel Laude, Peter Ochs, Daniel Cremers

We systematically study the local single-valuedness of the Bregman proximal mapping and local smoothness of the Bregman--Moreau envelope of a nonconvex function under relative prox…

math.OC20191 cited

Optimization of Inf-Convolution Regularized Nonconvex Composite Problems

Emanuel Laude, Tao Wu, Daniel Cremers

In this work, we consider nonconvex composite problems that involve inf-convolution with a Legendre function, which gives rise to an anisotropic generalization of the proximal mapp…

math.OC2018

A Nonlinear Bregman Primal-Dual Framework for Optimizing Nonconvex Infimal Convolutions

Emanuel Laude, Daniel Cremers

This work is concerned with the optimization of nonconvex, nonsmooth composite optimization problems, whose objective is a composition of a nonlinear mapping and a nonsmooth noncon…