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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
1592017
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
1182019
Quadruplet-wise Image Similarity Learning
MT Law, N Thome, M Cord
The IEEE International Conference on Computer Vision (ICCV), 2013
1082013
Lorentzian distance learning for hyperbolic representations
M Law, R Liao, J Snell, R Zemel
International Conference on Machine Learning, 3672-3681, 2019
1032019
A Theoretical Analysis of the Number of Shots in Few-Shot Learning
T Cao, MT Law, S Fidler
International Conference on Learning Representations, 2020
832020
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
752019
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
702021
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
472014
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
362021
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
242021
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
Optimizing Data Collection for Machine Learning
R Mahmood, J Lucas, JM Alvarez, S Fidler, MT Law
Advances in Neural Information Processing Systems, 2022
182022
Ultrahyperbolic Representation Learning
M Law, J Stam
Advances in Neural Information Processing Systems 33, 2020
182020
Ultrahyperbolic Neural Networks
MT Law
Advances in Neural Information Processing Systems 34, 2021
162021
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
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
152019
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Articles 1–20