Ariel Gordon

According to our database, Ariel Gordon authored at least 12 papers between 2016 and 2021.

Collaborative distances:

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

2021

Taskology: Utilizing Task Relations at Scale.

Yao Lu, Sören Pirk, Jan Dlabal, Anthony Brohan, Ankita Pasad, Zhao Chen, Vincent Casser, Anelia Angelova, Ariel Gordon

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Detecting Deficient Coverage in Colonoscopies.

Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin

IEEE Trans. Medical Imaging, 2020

Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos.

Ankita Pasad, Ariel Gordon, Tsung-Yi Lin, Anelia Angelova

CoRR, 2020

What Matters in Unsupervised Optical Flow.

Rico Jonschkowski, Austin Stone, Jonathan T. Barron, Ariel Gordon, Kurt Konolige, Anelia Angelova

Proceedings of the Computer Vision - ECCV 2020, 2020

Unsupervised Monocular Depth Learning in Dynamic Scenes.

Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Computationally Efficient Neural Image Compression.

Nick Johnston, Elad Eban, Ariel Gordon, Johannes Ballé

CoRR, 2019

Large-Scale Training Framework for Video Annotation.

Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Apostol Natsev

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Depth From Videos in the Wild: Unsupervised Monocular Depth Learning From Unknown Cameras.

Ariel Gordon, Hanhan Li, Rico Jonschkowski, Anelia Angelova

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks.

Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, Edward Choi

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks.

Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Tien-Ju Yang, Edward Choi

CoRR, 2017

Scalable Learning of Non-Decomposable Objectives.

Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Large-scale Learning With Global Non-Decomposable Objectives.

Elad Eban, Mariano Schain, Ariel Gordon, Rif Saurous, Gal Elidan

CoRR, 2016