AISTATS'20"A Primal-Dual Solver for Large-Scale Tracking-by-Assignment", Haller, Stefan and Prakash, Mangal and Hutschenreiter, Lisa and Pietzsch, Tobias and Rother, Carsten and Jug, Florian and Swoboda, Paul and Savchynskyy, Bogdan, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 2020
CVPR'19"A Convex Relaxation for Multi-Graph Matching", Swoboda, Paul and Mokarian, Ashkan and Theobalt, Christian and Bernard, Florian and others, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019
TPAMI'16"Partial Optimality by Pruning for MAP", Swoboda, Paul and Shekhovtsov, Alexander and Kappes, Jörg Hendrik and Schnörr, Christoph and Savchynskyy, Bogdan, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2016
CVPR'14"Partial optimality by pruning for MAP", Swoboda, Paul and Savchynskyy, Bogdan and Kappes, Jörg H and Schnörr, Christoph, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014, Best student paper award
We offer a PhD position for exceptionally gifted students. The position is fully funded (E13 TV-L) at the Heinrich Heine University Düsseldorf, Germany.
Tasks: Curiosity-driven basic research of fundamental problems in machine learning. Exemplary research areas include, but are not limited to, theoretically principled improvement of machine learning models, machine learning for optimization and efficient GPU algorithms.
Requirements: Very good university degree in mathematics, computer science or a related discipline, good programming skills, preferably python and C++.