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An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems



Andrea Gesmundo , Jeff Dean


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muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems



Andrea Gesmundo , Jeff Dean


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Scaling Up Models and Data with $\texttt{t5x}$ and $\texttt{seqio}$



Adam Roberts , Hyung Won Chung , Anselm Levskaya , Gaurav Mishra , James Bradbury , Daniel Andor , Sharan Narang , Brian Lester , Colin Gaffney , Afroz Mohiuddin , Curtis Hawthorne , Aitor Lewkowycz , Alex Salcianu , Marc van Zee , Jacob Austin , Sebastian Goodman , Livio Baldini Soares , Haitang Hu , Sasha Tsvyashchenko , Aakanksha Chowdhery , Jasmijn Bastings , Jannis Bulian , Xavier Garcia , Jianmo Ni , Andrew Chen , Kathleen Kenealy , Jonathan H. Clark , Stephan Lee , Dan Garrette , James Lee-Thorp , Colin Raffel , Noam Shazeer , Marvin Ritter , Maarten Bosma , Alexandre Passos , Jeremy Maitin-Shepard , Noah Fiedel , Mark Omernick , Brennan Saeta , Ryan Sepassi , Alexander Spiridonov , Joshua Newlan , Andrea Gesmundo


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Routing Networks with Co-training for Continual Learning



Mark Collier , Efi Kokiopoulou , Andrea Gesmundo , Jesse Berent

* Presented at ICML Workshop on Continual Learning 2020 

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Ranking architectures using meta-learning



Alina Dubatovka , Efi Kokiopoulou , Luciano Sbaiz , Andrea Gesmundo , Gabor Bartok , Jesse Berent

* NeurIPS 2019 Meta-Learning workshop 

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Gumbel-Matrix Routing for Flexible Multi-task Learning



Krzysztof Maziarz , Efi Kokiopoulou , Andrea Gesmundo , Luciano Sbaiz , Gabor Bartok , Jesse Berent


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Temporal coding in spiking neural networks with alpha synaptic function



Iulia M. Comsa , Krzysztof Potempa , Luca Versari , Thomas Fischbacher , Andrea Gesmundo , Jyrki Alakuijala

* Open-source code related to this paper is available at https://github.com/google/ihmehimmeli v2: Added references and added some clarifications for the methods 

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