Rafid Mahmood

According to our database, Rafid Mahmood authored at least 23 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Uncertainty Estimation for 3D Object Detection via Evidential Learning.

Nikita Durasov, Rafid Mahmood, Jiwoong Choi, Marc T. Law, James Lucas, Pascal Fua, José M. Álvarez

CoRR, 2024

No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine Annotation for Cost-Effective Understanding of Visual Data.

Christopher Klugmann, Rafid Mahmood, Guruprasad Hegde, Amit Kale, Daniel Kondermann

CoRR, 2024

AutoScale: Automatic Prediction of Compute-optimal Data Composition for Training LLMs.

Feiyang Kang, Yifan Sun, Bingbing Wen, Si Chen, Dawn Song, Rafid Mahmood, Ruoxi Jia

CoRR, 2024

Can Feedback Enhance Semantic Grounding in Large Vision-Language Models?

Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler, David Acuna

CoRR, 2024

Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets.

Yuan-Hong Liao, David Acuna, Rafid Mahmood, James Lucas, Viraj Prabhu, Sanja Fidler

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models.

Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler, David Acuna

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting.

Viraj Prabhu, David Acuna, Rafid Mahmood, Marc T. Law, Yuan-Hong Liao, Judy Hoffman, Sanja Fidler, James Lucas

Trans. Mach. Learn. Res., 2023

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting.

Viraj Prabhu, David Acuna, Andrew Liao, Rafid Mahmood, Marc T. Law, Judy Hoffman, Sanja Fidler, James Lucas

CoRR, 2023

2022

OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines.

Aaron Babier, Rafid Mahmood, Binghao Zhang, Victor Gabriel Leandro Alves, Ana Maria Barragán-Montero, Joel Beaudry, Carlos E. Cardenas S., Yankui Chang, Zijie Chen, Jaehee Chun, Kelly Diaz, Harold David Eraso, Erik Faustmann, Sibaji Gaj, Skylar S. Gay, Mary Gronberg, Bingqi Guo, Junjun He, Gerd Heilemann, Sanchit Hira, Yuliang Huang, Fuxin Ji, Dashan Jiang, Jean Carlo Jimenez Giraldo, Hoyeon Lee, Jun Lian, Shuolin Liu, Keng-Chi Liu, José Marrugo, Kentaro Miki, Kunio Nakamura, Tucker J. Netherton, Dan Nguyen, Hamidreza Nourzadeh, Alexander F. I. Osman, Zhao Peng, José Darío Quinto Muñoz, Christian Ramsl, Dong Joo Rhee, Juan David Rodriguez, Hongming Shan, Jeffrey V. Siebers, Mumtaz Hussain Soomro, Kay Sun, Andrés Usuga Hoyos, Carlos Valderrama, Rob Verbeek, Enpei Wang, Siri Willems, Qi Wu, Xuanang Xu, Sen Yang, Lulin Yuan, Simeng Zhu, Lukas Zimmermann, Kevin L. Moore, Thomas G. Purdie, Andrea L. McNiven, Timothy C. Y. Chan

CoRR, 2022

Optimizing Data Collection for Machine Learning.

Rafid Mahmood, James Lucas, José M. Álvarez, Sanja Fidler, Marc T. Law

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach.

Rafid Mahmood, Sanja Fidler, Marc T. Law

Proceedings of the Tenth International Conference on Learning Representations, 2022

How Much More Data Do I Need? Estimating Requirements for Downstream Tasks.

Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, José M. Álvarez, Zhiding Yu, Sanja Fidler, Marc T. Law

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization.

Aaron Babier, Timothy C. Y. Chan, Taewoo Lee, Rafid Mahmood, Daria Terekhov

INFORMS J. Optim., January, 2021

2020

Sampling from the complement of a polyhedron: An MCMC algorithm for data augmentation.

Timothy C. Y. Chan, Adam Diamant, Rafid Mahmood

Oper. Res. Lett., 2020

AutoAudio: Deep Learning for Automatic Audiogram Interpretation.

Matthew G. Crowson, Jong Wook Lee, Amr Hamour, Rafid Mahmood, Aaron Babier, Vincent Lin, Debara L. Tucci, Timothy C. Y. Chan

J. Medical Syst., 2020

OpenKBP: The open-access knowledge-based planning grand challenge.

Aaron Babier, Binghao Zhang, Rafid Mahmood, Kevin L. Moore, Thomas G. Purdie, Andrea L. McNiven, Timothy C. Y. Chan

CoRR, 2020

2019

The importance of evaluating the complete automated knowledge-based planning pipeline.

Aaron Babier, Rafid Mahmood, Andrea L. McNiven, Adam Diamant, Timothy C. Y. Chan

CoRR, 2019

2018

Streaming Codes for Multiplicative-Matrix Channels With Burst Rank Loss.

Rafid Mahmood, Ahmed Badr, Ashish Khisti

IEEE Trans. Inf. Theory, 2018

Interior Point Methods with Adversarial Networks.

Rafid Mahmood, Aaron Babier, Adam Diamant, Timothy C. Y. Chan

CoRR, 2018

Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks.

Rafid Mahmood, Aaron Babier, Andrea McNiven, Adam Diamant, Timothy C. Y. Chan

Proceedings of the Machine Learning for Healthcare Conference, 2018

2016

Convolutional Codes With Maximum Column Sum Rank for Network Streaming.

Rafid Mahmood, Ahmed Badr, Ashish Khisti

IEEE Trans. Inf. Theory, 2016

Low delay network streaming under burst losses.

Rafid Mahmood, Ahmed Badr, Ashish Khisti

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

Embedded MDS codes for multicast streaming.

Ahmed Badr, Rafid Mahmood, Ashish Khisti

Proceedings of the IEEE International Symposium on Information Theory, 2015