Mark Sandler

Mark Sandler

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Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning
Max Vladymyrov
Andrey Zhmoginov
Mark Sandler
(2024)
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
Andrey Zhmoginov
Mark Sandler
Max Vladymyrov
ICML (2022)
Fine-Tuning Image Transformers Using Learnable Memory
Andrew Jackson
Andrey Zhmoginov
Mark Sandler
Max Vladymyrov
CVPR 2022
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks
Andrey Zhmoginov
Dina Bashkirova
Mark Sandler
arXiv (2021)
Meta-Learning Bidirectional Update Rules
Mark Sandler
Max Vladymyrov
Andrey Zhmoginov
Nolan Andrew Miller
Andrew Jackson
Tom Madams
Blaise Hilary Aguera-Arcas
ICML 2021
Estimating the Changing Infection Rate of COVID-19 Using Bayesian Models of Mobility
Luyang Liu
Sharad Vikram
Junpeng Lao
Xue Ben
Alexander Nicholas D'Amour
Shawn O'Banion
Mark Sandler
Rif A. Saurous
Matthew D. Hoffman
medRxiv, https://www.medrxiv.org/content/10.1101/2020.08.06.20169664v1.full (2020)
SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection
Keren Ye
Adriana Kovashka
Mark Sandler
Menglong Zhu
Andrew Howard
Marco Fornoni
Proceedings of the Asian Conference on Computer Vision (ACCV), Springer (2020)
MnasNet: Platform-Aware Neural Architecture Search for Mobile
Mingxing Tan
Bo Chen
Ruoming Pang
Vijay Vasudevan
Mark Sandler
Andrew Howard
Quoc V. Le
CVPR (2019)
Non-discriminative data or weak model? On the relative importance of data and model resolution
Andrew Howard
Andrey Zhmoginov
Jonathan Michael Baccash
Mark Sandler
ICCV (2019)
Structured Multi-Hashing for Model Compression
Elad Eban
Yair Movshovitz-Attias
Hao Wu
Mark Sandler
Andrew Poon
Yerlan Idelbayev
Miguel A. Carreira-Perpinan
(2019)
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