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Faculty of Informatics
Technical University of Munich

Technical University of Munich

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Emanuel Laude

PhD StudentTechnische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17790
Fax: +49-89-289-17757
Office: 02.09.039
Mail: emanuel.laude@in.tum.de

Emanuel Laude

Research Interests

Convex and Nonconvex Optimization for Machine Learning and Computer Vision, Convex Relaxation Methods

Bio

I'm a second-year PhD student in computer science at the Computer Vision Group TUM headed by Prof. Daniel Cremers. In my research I focus on Convex and Nonconvex Optimization for Machine Learning and Computer Vision and Convex Relaxation Methods.

I received my Master's degree (with high distinction) in Informatics (minor Mathematics) in 2015 from the Technical University of Munich and my Bachelor's degree (with distinction) in Computer Science in 2013 from the University of Würzburg.

Publications

Conference and Workshop Papers
2017
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization (E. Laude, T. Wu, D. Cremers), In arXiv preprint, 2017. [bib] [pdf]
Discrete-Continuous Splitting for Weakly Supervised Learning (E. Laude, J.-H. Lange, F. R. Schmidt, B. Andres, D. Cremers), In arXiv preprint, 2017. [bib] [pdf]
2016
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies (E. Laude, T. Möllenhoff, M. Moeller, J. Lellmann, D. Cremers), In European Conference on Computer Vision (ECCV), 2016.([supp] [code]) [bib] [pdf]
Sublabel-Accurate Relaxation of Nonconvex Energies (T. Möllenhoff, E. Laude, M. Moeller, J. Lellmann, D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.([supp] [code]) [bib] [pdf]Oral Presentation, Received the Best Paper Honorable Mention Award at CVPR 2016
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Teaching

Winter Term 2017/18

Summer Term 2017

Summer Term 2016

Rechte Seite

Informatik IX
Chair for Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de