Marc T. Law
Marc T. Law
Research Scientist at NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Quadruplet-wise Image Similarity Learning
MT Law, N Thome, M Cord
The IEEE International Conference on Computer Vision (ICCV), 2013
782013
Deep Spectral Clustering Learning
MT Law, R Urtasun, RS Zemel
International Conference on Machine Learning (ICML), 2017
742017
Fantope Regularization in Metric Learning
MT Law, N Thome, M Cord
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014
332014
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
312019
Bag-of-words image representation: Key ideas and further insight
MT Law, N Thome, M Cord
Fusion in Computer Vision, 29-52, 2014
292014
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
232017
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
192016
Structural and visual comparisons for web page archiving
MT Law, N Thome, S Gançarski, M Cord
Proceedings of the 2012 ACM symposium on Document engineering, 117-120, 2012
142012
Hybrid pooling fusion in the bow pipeline
M Law, N Thome, M Cord
European Conference on Computer Vision, 355-364, 2012
122012
Structural and visual similarity learning for web page archiving
MT Law, CS Gutierrez, N Thome, S Gançarski, M Cord
2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI …, 2012
122012
Video face clustering with unknown number of clusters
M Tapaswi, MT Law, S Fidler
Proceedings of the IEEE International Conference on Computer Vision, 5027-5036, 2019
102019
Dimensionality reduction for representing the knowledge of probabilistic models
MT Law, J Snell, A Farahmand, R Urtasun, RS Zemel
International Conference on Learning Representations, 2019
92019
Efficient Multiple Instance Metric Learning using Weakly Supervised Data
MT Law, Y Yu, R Urtasun, RS Zemel, EP Xing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
92017
Lorentzian distance learning for hyperbolic representations
M Law, R Liao, J Snell, R Zemel
International Conference on Machine Learning, 3672-3681, 2019
72019
A Theoretical Analysis of the Number of Shots in Few-Shot Learning
T Cao, MT Law, S Fidler
International Conference on Learning Representations, 2020
42020
Lorentzian Distance Learning
MT Law, J Snell, RS Zemel
12018
Ultrahyperbolic Representation Learning
MT Law, J Stam
arXiv preprint arXiv:2007.00211, 2020
2020
Representing Relative Visual Attributes with a Reference-Point-Based Decision Model
MT Law, P Weng
2018 24th International Conference on Pattern Recognition (ICPR), 435-440, 2018
2018
Supplementary Material of Deep Spectral Clustering Learning
MT Law, R Urtasun, RS Zemel
epsilon 10 (7), 13, 2017
2017
Apprentissage de métrique appliqué à la détection de changement de page Web et aux attributs relatifs
MT Law, N Thome, S Gançarski, M Cord
2015
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Articles 1–20