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Marc T. Law
Marc T. Law
Research Scientist at NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Deep Spectral Clustering Learning
MT Law, R Urtasun, RS Zemel
International Conference on Machine Learning (ICML), 2017
1552017
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
1142019
Quadruplet-wise Image Similarity Learning
MT Law, N Thome, M Cord
The IEEE International Conference on Computer Vision (ICCV), 2013
1102013
Lorentzian distance learning for hyperbolic representations
M Law, R Liao, J Snell, R Zemel
International Conference on Machine Learning, 3672-3681, 2019
972019
A Theoretical Analysis of the Number of Shots in Few-Shot Learning
T Cao, MT Law, S Fidler
International Conference on Learning Representations, 2020
822020
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
732019
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
642021
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
462014
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
412017
Fantope Regularization in Metric Learning
MT Law, N Thome, M Cord
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014
412014
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
R Mahmood, S Fidler, MT Law
arXiv preprint arXiv:2106.02968, 2021
332021
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
272016
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
222021
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
192022
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
192012
Ultrahyperbolic Representation Learning
M Law, J Stam
Advances in Neural Information Processing Systems 33, 2020
172020
Optimizing Data Collection for Machine Learning
R Mahmood, J Lucas, JM Alvarez, S Fidler, MT Law
Advances in Neural Information Processing Systems, 2022
162022
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
162012
Ultrahyperbolic Neural Networks
MT Law
Advances in Neural Information Processing Systems 34, 2021
152021
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
142019
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Articles 1–20