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Max Vladymyrov
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Continual Few-Shot Learning Using HyperTransformers


Jan 12, 2023
Max Vladymyrov, Andrey Zhmoginov, Mark Sandler

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Training trajectories, mini-batch losses and the curious role of the learning rate


Jan 05, 2023
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Nolan Miller

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* 21 pages, 14 figures 
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Transformers learn in-context by gradient descent


Dec 15, 2022
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov

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Decentralized Learning with Multi-Headed Distillation


Nov 28, 2022
Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov

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Fine-tuning Image Transformers using Learnable Memory


Mar 30, 2022
Mark Sandler, Andrey Zhmoginov, Max Vladymyrov, Andrew Jackson

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* CVPR 2022, to appear 
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HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning


Jan 15, 2022
Andrey Zhmoginov, Mark Sandler, Max Vladymyrov

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GradMax: Growing Neural Networks using Gradient Information


Jan 13, 2022
Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa

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Meta-Learning Bidirectional Update Rules


Apr 10, 2021
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Aguera y Arcas

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Underspecification Presents Challenges for Credibility in Modern Machine Learning


Nov 06, 2020
Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

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