| Learning using privileged information: SVM+ and weighted SVM M Lapin, M Hein, B Schiele Neural Networks 53, 95-108, 2014 | 156 | 2014 |
| Analysis and optimization of loss functions for multiclass, top-k, and multilabel classification M Lapin, M Hein, B Schiele IEEE transactions on pattern analysis and machine intelligence 40 (7), 1533-1554, 2017 | 103 | 2017 |
| Top-k Multiclass SVM M Lapin, M Hein, B Schiele Advances in Neural Information Processing Systems (NIPS 2015), 325-333, 2015 | 95 | 2015 |
| Loss Functions for Top-k Error: Analysis and Insights M Lapin, M Hein, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), 2016 | 94 | 2016 |
| Scalable Multitask Representation Learning for Scene Classification M Lapin, B Schiele, M Hein IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), 2014 | 56 | 2014 |
| Efficient Output Kernel Learning for Multiple Tasks P Jawanpuria, M Lapin, M Hein, B Schiele Advances in Neural Information Processing Systems (NIPS 2015), 1189-1197, 2015 | 35 | 2015 |
| SHAVE: stochastic hybrid analysis of markov population models M Lapin, L Mikeev, V Wolf Proceedings of the 14th international conference on Hybrid systems …, 2011 | 26 | 2011 |
| Contrastive language-action pre-training for temporal localization M Xu, E Gundogdu, M Lapin, B Ghanem, M Donoser, L Bazzani arXiv preprint arXiv:2204.12293, 2022 | 5 | 2022 |
| Machine learning system to score alt-text in image data L Bazzani, M Lapin, F Hieber, T Domhan US Patent 11,361,212, 2022 | 3 | 2022 |
| Image classification with limited training data and class ambiguity M Lapin | 1 | 2017 |
| Simplex Coding and Supervised Dictionary Learning M Lapin Saarland University, 2012 | | 2012 |
| Scalable Multitask Representation Learning for Scene Classification Supplementary Material M Lapin, B Schiele, M Hein | | |
Matthias HeinProfessor of Computer Science, University of Tübingen確認したメール アドレス: uni-tuebingen.de
