| Software defect prediction using ensemble learning on selected features IH Laradji, M Alshayeb, L Ghouti Information and Software Technology 58, 388-402, 2015 | 240 | 2015 |
| Coordinate descent converges faster with the gauss-southwell rule than random selection J Nutini, M Schmidt, I Laradji, M Friedlander, H Koepke International Conference on Machine Learning (ICML), 1632-1641, 2015 | 168 | 2015 |
| Where are the blobs: Counting by localization with point supervision IH Laradji, N Rostamzadeh, PO Pinheiro, D Vazquez, M Schmidt Proceedings of the European Conference on Computer Vision (ECCV), 547-562, 2018 | 70 | 2018 |
| Painless stochastic gradient: Interpolation, line-search, and convergence rates S Vaswani, A Mishkin, I Laradji, M Schmidt, G Gidel, S Lacoste-Julien arXiv preprint arXiv:1905.09997, 2019 | 53 | 2019 |
| Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence J Nutini, I Laradji, M Schmidt arXiv preprint arXiv:1712.08859, 2017 | 33 | 2017 |
| Perceptual hashing of color images using hypercomplex representations IH Laradji, L Ghouti, EH Khiari 2013 IEEE International Conference on Image Processing, 4402-4406, 2013 | 26 | 2013 |
| Convergence rates for greedy Kaczmarz algorithms, and faster randomized Kaczmarz rules using the orthogonality graph J Nutini, B Sepehry, I Laradji, M Schmidt, H Koepke, A Virani arXiv preprint arXiv:1612.07838, 2016 | 25 | 2016 |
| M-ADDA: Unsupervised domain adaptation with deep metric learning IH Laradji, R Babanezhad Domain adaptation for visual understanding, 17-31, 2020 | 19 | 2020 |
| Where are the masks: Instance segmentation with image-level supervision IH Laradji, D Vazquez, M Schmidt arXiv preprint arXiv:1907.01430, 2019 | 18 | 2019 |
| Stochastic polyak step-size for SGD: An adaptive learning rate for fast convergence N Loizou, S Vaswani, I Laradji, S Lacoste-Julien arXiv preprint arXiv:2002.10542, 2020 | 15 | 2020 |
| Online fast adaptation and knowledge accumulation: a new approach to continual learning M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, L Caccia, ... arXiv preprint arXiv:2003.05856, 2020 | 14 | 2020 |
| Embedding propagation: Smoother manifold for few-shot classification P Rodríguez, I Laradji, A Drouin, A Lacoste European Conference on Computer Vision, 121-138, 2020 | 13 | 2020 |
| Convergence rates for greedy Kaczmarz algorithms J Nutini, B Sepehry, A Virani, I Laradji, M Schmidt, H Koepke Conference on Uncertainty in Artificial Intelligence, 2016 | 9 | 2016 |
| A weakly supervised consistency-based learning method for covid-19 segmentation in ct images I Laradji, P Rodriguez, O Manas, K Lensink, M Law, L Kurzman, W Parker, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 7 | 2021 |
| A weakly supervised region-based active learning method for covid-19 segmentation in ct images I Laradji, P Rodriguez, F Branchaud-Charron, K Lensink, P Atighehchian, ... arXiv preprint arXiv:2007.07012, 2020 | 7 | 2020 |
| Fast and furious convergence: Stochastic second order methods under interpolation SY Meng, S Vaswani, IH Laradji, M Schmidt, S Lacoste-Julien International Conference on Artificial Intelligence and Statistics, 1375-1386, 2020 | 6 | 2020 |
| Instance segmentation with point supervision IH Laradji, N Rostamzadeh, PO Pinheiro, D Vázquez, M Schmidt arXiv preprint arXiv:1906.06392, 2019 | 5 | 2019 |
| Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search) S Vaswani, I Laradji, F Kunstner, SY Meng, M Schmidt, S Lacoste-Julien arXiv preprint arXiv:2006.06835, 2020 | 4 | 2020 |
| Masaga: a linearly-convergent stochastic first-order method for optimization on manifolds R Babanezhad, IH Laradji, A Shafaei, M Schmidt Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 4 | 2018 |
| Learning data augmentation with online bilevel optimization for image classification S Mounsaveng, I Laradji, I Ben Ayed, D Vazquez, M Pedersoli Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 3 | 2021 |
Mark SchmidtAssociate Professor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
