| Unsupervised domain adaptation by domain invariant projection M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann Proceedings of the IEEE International Conference on Computer Vision, 769-776, 2013 | 237 | 2013 |
| Domain adaptation on the statistical manifold M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 61 | 2014 |
| Distribution-matching embedding for visual domain adaptation M Baktashmotlagh, M Harandi, M Salzmann The Journal of Machine Learning Research 17 (1), 3760-3789, 2016 | 32 | 2016 |
| Beyond gauss: Image-set matching on the riemannian manifold of pdfs M Harandi, M Salzmann, M Baktashmotlagh Proceedings of the IEEE International Conference on Computer Vision, 4112-4120, 2015 | 32 | 2015 |
| Domain adaptation in computer vision applications G Csurka Springer, 2017 | 30 | 2017 |
| Discriminative non-linear stationary subspace analysis for video classification M Baktashmotlagh, M Harandi, BC Lovell, M Salzmann IEEE transactions on pattern analysis and machine intelligence 36 (12), 2353 …, 2014 | 24 | 2014 |
| R1SVM: a Randomised Nonlinear Approach to Large-Scale Anomaly Detection S Erfani, M Baktashmotlagh, S Rajasegarar, S Karunasekera, C Leckie Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 23 | 2015 |
| Directional space-time oriented gradients for 3d visual pattern analysis E Norouznezhad, MT Harandi, A Bigdeli, M Baktash, A Postula, BC Lovell European Conference on Computer Vision, 736-749, 2012 | 18 | 2012 |
| Robust domain generalisation by enforcing distribution invariance S Erfani, M Baktashmotlagh, M Moshtaghi, V Nguyen, C Leckie, J Bailey, ... Proceedings of the Twenty-Fifth International Joint Conference on Artificial …, 2016 | 10 | 2016 |
| R1STM: One-class support tensor machine with randomised kernel SM Erfani, M Baktashmotlagh, S Rajasegarad, V Nguyen, C Leckie, ... Proceedings of the 2016 SIAM International Conference on Data Mining, 198-206, 2016 | 9 | 2016 |
| Non-linear stationary subspace analysis with application to video classification M Baktashmotlagh, M Harandi, A Bigdeli, B Lovell, M Salzmann International Conference on Machine Learning, 450-458, 2013 | 8 | 2013 |
| Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs M Baktashmotlagh, A Bigdeli, BC Lovell 2011 8th IEEE International Conference on Advanced Video and Signal Based …, 2011 | 7 | 2011 |
| Learning factorized representations for open-set domain adaptation M Baktashmotlagh, M Faraki, T Drummond, M Salzmann arXiv preprint arXiv:1805.12277, 2018 | 4 | 2018 |
| Deep discovery of facial motions using a shallow embedding layer A Ghasemi, M Baktashmotlagh, S Denman, S Sridharan, DN Tien, ... 2017 IEEE International Conference on Image Processing (ICIP), 1567-1571, 2017 | 4 | 2017 |
| From shared subspaces to shared landmarks: A robust multi-source classification approach SM Erfani, M Baktashmotlagh, M Moshtaghi, V Nguyen, C Leckie, J Bailey, ... Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 3 | 2017 |
| Linking numerical scores with sentiment analysis of students' teaching and subject evaluation surveys: Pointers to teaching enhancements S Cunningham-Nelson, M Baktashmotlagh, W Boles 27th Annual Conference of the Australasian Association for Engineering …, 2016 | 3 | 2016 |
| Deep Level Sets: Implicit Surface Representations for 3D Shape Inference M Michalkiewicz, JK Pontes, D Jack, M Baktashmotlagh, A Eriksson arXiv preprint arXiv:1901.06802, 2019 | 2 | 2019 |
| On Minimum Discrepancy Estimation for Deep Domain Adaptation MM Rahman, C Fookes, M Baktashmotlagh, S Sridharan arXiv preprint arXiv:1901.00282, 2019 | 2 | 2019 |
| On Encoding Temporal Evolution for Real-time Action Prediction F Rezazadegan, S Shirazi, M Baktashmotlagh, LS Davis arXiv preprint arXiv:1709.07894, 2017 | 2 | 2017 |
| Visualising student satisfaction S Cunningham-Nelson, M Baktashmotlagh, W Boles 28th Annual Conference of the Australasian Association for Engineering …, 2017 | 2 | 2017 |
Mathieu SalzmannEPFLVerified email at epfl.ch
