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Task Selection for AutoML System Evaluation


Aug 26, 2022
Jonathan Lorraine, Nihesh Anderson, Chansoo Lee, Quentin De Laroussilhe, Mehadi Hassen

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Lyapunov Exponents for Diversity in Differentiable Games


Dec 24, 2021
Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob Foerster

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* AAMAS2022, 24 pages 

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Input Convex Gradient Networks


Nov 23, 2021
Jack Richter-Powell, Jonathan Lorraine, Brandon Amos

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* Accepted to NeurIPS 2021 Optimal Transport and Machine Learning Workshop https://otml2021.github.io 

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Meta-Learning to Improve Pre-Training


Nov 02, 2021
Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud

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* NeurIPS 2021 

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Complex Momentum for Learning in Games


Feb 16, 2021
Jonathan Lorraine, David Acuna, Paul Vicol, David Duvenaud

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Optimizing Millions of Hyperparameters by Implicit Differentiation


Nov 06, 2019
Jonathan Lorraine, Paul Vicol, David Duvenaud

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* Submitted to AISTATS 2020 

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Understanding Neural Architecture Search Techniques


Mar 31, 2019
George Adam, Jonathan Lorraine

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Stochastic Hyperparameter Optimization through Hypernetworks


Mar 08, 2018
Jonathan Lorraine, David Duvenaud

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* 9 pages, 6 figures; revised figures 

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