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Marc T. Law
Person information
- affiliation: NVIDIA Toronto AI Lab, ON, Canada
- affiliation: University of Toronto, Canada
- affiliation: Vector Institute, Toronto, ON, Canada
- affiliation (PhD 2015): Pierre and Marie Curie University, Paris, France
- affiliation: Sorbonne University, LIP6, Paris, France
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2020 – today
- 2024
- [c26]Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine
, James Lucas:
Graph Metanetworks for Processing Diverse Neural Architectures. ICLR 2024 - [i16]Haitz Sáez de Ocáriz Borde, Takashi Furuya, Anastasis Kratsios, Marc T. Law:
Breaking the Curse of Dimensionality with Distributed Neural Computation. CoRR abs/2402.03460 (2024) - [i15]Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein:
Neural Spacetimes for DAG Representation Learning. CoRR abs/2408.13885 (2024) - [i14]Tianchang Shen, Zhaoshuo Li, Marc T. Law, Matan Atzmon, Sanja Fidler, James Lucas, Jun Gao, Nicholas Sharp:
SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes. CoRR abs/2409.20562 (2024) - 2023
- [j2]Viraj Prabhu, David Acuna, Rafid Mahmood, Marc T. Law, Yuan-Hong Liao, Judy Hoffman, Sanja Fidler, James Lucas:
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. Trans. Mach. Learn. Res. 2023 (2023) - [c25]Marc T. Law, James Lucas:
Spacetime Representation Learning. ICLR 2023 - [i13]Viraj Prabhu, David Acuna, Andrew Liao, Rafid Mahmood, Marc T. Law, Judy Hoffman, Sanja Fidler, James Lucas:
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. CoRR abs/2302.04832 (2023) - [i12]Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas:
Graph Metanetworks for Processing Diverse Neural Architectures. CoRR abs/2312.04501 (2023) - 2022
- [c24]Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, José M. Álvarez, Zhiding Yu, Sanja Fidler, Marc T. Law:
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. CVPR 2022: 275-284 - [c23]David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler:
Domain Adversarial Training: A Game Perspective. ICLR 2022 - [c22]Rafid Mahmood, Sanja Fidler, Marc T. Law:
Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. ICLR 2022 - [c21]Rafid Mahmood, James Lucas, José M. Álvarez, Sanja Fidler, Marc T. Law:
Optimizing Data Collection for Machine Learning. NeurIPS 2022 - [i11]David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler:
Domain Adversarial Training: A Game Perspective. CoRR abs/2202.05352 (2022) - [i10]Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, José M. Álvarez, Zhiding Yu, Sanja Fidler, Marc T. Law:
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. CoRR abs/2207.01725 (2022) - [i9]Rafid Mahmood, James Lucas, José M. Álvarez, Sanja Fidler, Marc T. Law:
Optimizing Data Collection for Machine Learning. CoRR abs/2210.01234 (2022) - 2021
- [c20]Aayush Prakash, Shoubhik Debnath, Jean-Francois Lafleche, Eric Cameracci, Gavriel State, Stan Birchfield, Marc T. Law:
Self-Supervised Real-to-Sim Scene Generation. ICCV 2021: 16024-16034 - [c19]David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler:
f-Domain Adversarial Learning: Theory and Algorithms. ICML 2021: 66-75 - [c18]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature generation for long-tail classification. ICVGIP 2021: 41:1-41:9 - [c17]Marc T. Law:
Ultrahyperbolic Neural Networks. NeurIPS 2021: 22058-22069 - [i8]Rafid Mahmood, Sanja Fidler, Marc T. Law:
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. CoRR abs/2106.02968 (2021) - [i7]David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler:
f-Domain-Adversarial Learning: Theory and Algorithms. CoRR abs/2106.11344 (2021) - [i6]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature Generation for Long-tail Classification. CoRR abs/2111.05956 (2021) - 2020
- [c16]Tianshi Cao, Marc T. Law, Sanja Fidler:
A Theoretical Analysis of the Number of Shots in Few-Shot Learning. ICLR 2020 - [c15]Marc T. Law, Jos Stam:
Ultrahyperbolic Representation Learning. NeurIPS 2020 - [i5]Marc T. Law, Jos Stam:
Ultrahyperbolic Representation Learning. CoRR abs/2007.00211 (2020) - [i4]Aayush Prakash, Shoubhik Debnath, Jean-Francois Lafleche, Eric Cameracci, Gavriel State, Marc T. Law:
Sim2SG: Sim-to-Real Scene Graph Generation for Transfer Learning. CoRR abs/2011.14488 (2020)
2010 – 2019
- 2019
- [c14]Jixuan Wang, Kuan-Chieh Wang, Marc T. Law, Frank Rudzicz, Michael Brudno:
Centroid-based Deep Metric Learning for Speaker Recognition. ICASSP 2019: 3652-3656 - [c13]Makarand Tapaswi, Marc T. Law, Sanja Fidler:
Video Face Clustering With Unknown Number of Clusters. ICCV 2019: 5026-5035 - [c12]Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel:
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. ICLR (Poster) 2019 - [c11]Marc Teva Law, Renjie Liao, Jake Snell, Richard S. Zemel:
Lorentzian Distance Learning for Hyperbolic Representations. ICML 2019: 3672-3681 - [i3]Jixuan Wang, Kuan-Chieh Wang, Marc T. Law, Frank Rudzicz, Michael Brudno:
Centroid-based deep metric learning for speaker recognition. CoRR abs/1902.02375 (2019) - [i2]Makarand Tapaswi, Marc T. Law, Sanja Fidler:
Video Face Clustering with Unknown Number of Clusters. CoRR abs/1908.03381 (2019) - [i1]Tianshi Cao
A Theoretical Analysis of the Number of Shots in Few-Shot Learning. CoRR abs/1909.11722 (2019) - 2018
- [c10]Marc T. Law, Paul Weng:
Representing Relative Visual Attributes with a Reference-Point-Based Decision Model. ICPR 2018: 435-440 - 2017
- [j1]Marc T. Law, Nicolas Thome, Matthieu Cord:
Learning a Distance Metric from Relative Comparisons between Quadruplets of Images. Int. J. Comput. Vis. 121(1): 65-94 (2017) - [c9]Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing:
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. CVPR 2017: 5948-5956 - [c8]Marc T. Law, Raquel Urtasun, Richard S. Zemel:
Deep Spectral Clustering Learning. ICML 2017: 1985-1994 - 2016
- [c7]Marc T. Law, Yaoliang Yu, Matthieu Cord, Eric P. Xing:
Closed-Form Training of Mahalanobis Distance for Supervised Clustering. CVPR 2016: 3909-3917 - 2015
- [b1]Marc Teva Law:
Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web). Pierre and Marie Curie University, Paris, France, 2015 - [c6]Marc Teva Law, Nicolas Thome, Stéphane Gançarski, Matthieu Cord:
Apprentissage de métrique appliqué à la détection de changement de page Web et aux attributs relatifs. CORIA 2015: 223-238 - 2014
- [c5]Marc T. Law, Nicolas Thome, Matthieu Cord:
Fantope Regularization in Metric Learning. CVPR 2014: 1051-1058 - [p1]Marc T. Law, Nicolas Thome, Matthieu Cord:
Bag-of-Words Image Representation: Key Ideas and Further Insight. Fusion in Computer Vision 2014: 29-52 - 2013
- [c4]Marc T. Law, Nicolas Thome, Matthieu Cord:
Quadruplet-Wise Image Similarity Learning. ICCV 2013: 249-256 - 2012
- [c3]Marc T. Law, Carlos Sureda Gutierrez, Nicolas Thome, Stéphane Gançarski:
Structural and visual similarity learning for Web page archiving. CBMI 2012: 1-6 - [c2]Marc Teva Law, Nicolas Thome, Stéphane Gançarski, Matthieu Cord:
Structural and visual comparisons for web page archiving. ACM Symposium on Document Engineering 2012: 117-120 - [c1]Marc T. Law, Nicolas Thome, Matthieu Cord:
Hybrid Pooling Fusion in the BoW Pipeline. ECCV Workshops (3) 2012: 355-364
Coauthor Index
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last updated on 2024-10-23 20:35 CEST by the dblp team
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