Marc T. Law

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 34

Top Topics

Supervised Clustering

Integer Programming

Metric Learning

Neural Architectures

Top Venues

Publications

Haitz Sáez de Ocáriz Borde, Takashi Furuya, Anastasis Kratsios, Marc T. Law
Breaking the Curse of Dimensionality with Distributed Neural Computation. CoRR (2024)
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
Graph Metanetworks for Processing Diverse Neural Architectures. ICLR (2024)
Marc T. Law, James Lucas
Spacetime Representation Learning. ICLR (2023)
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)
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 (2023)
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
Graph Metanetworks for Processing Diverse Neural Architectures. CoRR (2023)
Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc T. Law
Optimizing Data Collection for Machine Learning. CoRR (2022)
Rafid Mahmood, Sanja Fidler, Marc T. Law
Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. ICLR (2022)
Rafid Mahmood, James Lucas, Jose M. Alvarez, Sanja Fidler, Marc T. Law
Optimizing Data Collection for Machine Learning. NeurIPS (2022)
Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, Jose M. Alvarez, Zhiding Yu, Sanja Fidler, Marc T. Law
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. CVPR (2022)
Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, Jose M. Alvarez, Zhiding Yu, Sanja Fidler, Marc T. Law
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. CoRR (2022)
David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler
Domain Adversarial Training: A Game Perspective. CoRR (2022)
David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler
Domain Adversarial Training: A Game Perspective. ICLR (2022)
Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi
Feature generation for long-tail classification. ICVGIP (2021)
Rafid Mahmood, Sanja Fidler, Marc T. Law
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. CoRR (2021)
David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler
f-Domain Adversarial Learning: Theory and Algorithms. ICML (2021)
David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler
f-Domain-Adversarial Learning: Theory and Algorithms. CoRR (2021)
Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi
Feature Generation for Long-tail Classification. CoRR (2021)
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)
Tianshi Cao, Marc T. Law, Sanja Fidler
A Theoretical Analysis of the Number of Shots in Few-Shot Learning. ICLR (2020)
Marc T. Law, Jos Stam
Ultrahyperbolic Representation Learning. NeurIPS (2020)
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 (2020)
Marc T. Law, Jos Stam
Ultrahyperbolic Representation Learning. CoRR (2020)
Makarand Tapaswi, Marc T. Law, Sanja Fidler
Video Face Clustering with Unknown Number of Clusters. CoRR (2019)
Tianshi Cao, Marc T. Law, Sanja Fidler
A Theoretical Analysis of the Number of Shots in Few-Shot Learning. CoRR (2019)
Jixuan Wang, Kuan-Chieh Wang, Marc T. Law, Frank Rudzicz, Michael Brudno
Centroid-based Deep Metric Learning for Speaker Recognition. ICASSP (2019)
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)
Jixuan Wang, Kuan-Chieh Wang, Marc T. Law, Frank Rudzicz, Michael Brudno
Centroid-based deep metric learning for speaker recognition. CoRR (2019)
Makarand Tapaswi, Marc T. Law, Sanja Fidler
Video Face Clustering With Unknown Number of Clusters. ICCV (2019)
Marc T. Law, Paul Weng
Representing Relative Visual Attributes with a Reference-Point-Based Decision Model. ICPR (2018)
Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. CVPR (2017)
Marc T. Law, Raquel Urtasun, Richard S. Zemel
Deep Spectral Clustering Learning. ICML (2017)
Marc T. Law, Nicolas Thome, Matthieu Cord
Learning a Distance Metric from Relative Comparisons between Quadruplets of Images. Int. J. Comput. Vis. 121 (1) (2017)
Marc T. Law, Yaoliang Yu, Matthieu Cord, Eric P. Xing
Closed-Form Training of Mahalanobis Distance for Supervised Clustering. CVPR (2016)
Marc T. Law, Nicolas Thome, Matthieu Cord
Fantope Regularization in Metric Learning. CVPR (2014)
Marc T. Law, Nicolas Thome, Matthieu Cord
Quadruplet-Wise Image Similarity Learning. ICCV (2013)
Marc T. Law, Nicolas Thome, Matthieu Cord
Hybrid Pooling Fusion in the BoW Pipeline. ECCV Workshops (3) (2012)
Marc T. Law, Carlos Sureda Gutierrez, Nicolas Thome, Stéphane Gançarski
Structural and visual similarity learning for Web page archiving. CBMI (2012)