| Deep Spectral Clustering Learning MT Law, R Urtasun, RS Zemel International Conference on Machine Learning (ICML), 2017 | 178 | 2017 |
| Lorentzian distance learning for hyperbolic representations M Law, R Liao, J Snell, R Zemel International Conference on Machine Learning, 3672-3681, 2019 | 164 | 2019 |
| Centroid-based deep metric learning for speaker recognition J Wang, KC Wang, MT Law, F Rudzicz, M Brudno ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 141 | 2019 |
| Quadruplet-wise Image Similarity Learning MT Law, N Thome, M Cord The IEEE International Conference on Computer Vision (ICCV), 2013 | 116 | 2013 |
| A Theoretical Analysis of the Number of Shots in Few-Shot Learning T Cao, MT Law, S Fidler International Conference on Learning Representations, 2020 | 110 | 2020 |
| f-Domain-Adversarial Learning: Theory and Algorithms D Acuna, G Zhang, MT Law, S Fidler International Conference on Machine Learning (ICML) 139, 3672-3681, 2021 | 109 | 2021 |
| Video face clustering with unknown number of clusters M Tapaswi, MT Law, S Fidler Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 85 | 2019 |
| Graph metanetworks for processing diverse neural architectures D Lim, H Maron, MT Law, J Lorraine, J Lucas arXiv preprint arXiv:2312.04501, 2023 | 53 | 2023 |
| Low budget active learning via wasserstein distance: An integer programming approach R Mahmood, S Fidler, MT Law arXiv preprint arXiv:2106.02968, 2021 | 50 | 2021 |
| How much more data do i need? estimating requirements for downstream tasks R Mahmood, J Lucas, D Acuna, D Li, J Philion, JM Alvarez, Z Yu, S Fidler, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 49 | 2022 |
| Learning a Distance Metric from Relative Comparisons between Quadruplets of Images MT Law, N Thome, M Cord International Journal of Computer Vision, 1-30, 2017 | 48 | 2017 |
| Optimizing Data Collection for Machine Learning R Mahmood, J Lucas, JM Alvarez, S Fidler, MT Law Advances in Neural Information Processing Systems, 2022 | 46 | 2022 |
| Bag-of-words image representation: Key ideas and further insight MT Law, N Thome, M Cord Fusion in Computer Vision: Understanding Complex Visual Content, 29-52, 2014 | 46 | 2014 |
| Fantope Regularization in Metric Learning MT Law, N Thome, M Cord Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014 | 43 | 2014 |
| Self-Supervised Real-to-Sim Scene Generation A Prakash, S Debnath, JF Lafleche, E Cameracci, G State, S Birchfield, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 33 | 2021 |
| Closed-Form Training of Mahalanobis Distance for Supervised Clustering MT Law, Y Yu, M Cord, EP Xing IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | 29 | 2016 |
| Ultrahyperbolic Representation Learning M Law, J Stam Advances in Neural Information Processing Systems 33, 2020 | 26 | 2020 |
| Ultrahyperbolic Neural Networks MT Law Advances in Neural Information Processing Systems 34, 2021 | 25 | 2021 |
| Feature generation for long-tail classification R Vigneswaran, MT Law, VN Balasubramanian, M Tapaswi Proceedings of the twelfth Indian conference on computer vision, graphics …, 2021 | 23 | 2021 |
| Domain Adversarial Training: A Game Perspective D Acuna, MT Law, G Zhang, S Fidler International Conference on Learning Representations, 2022 | 18 | 2022 |
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
