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Alexandre Passos

UMass Amherst

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


Mar 31, 2022
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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FRUIT: Faithfully Reflecting Updated Information in Text


Dec 16, 2021
Robert L. Logan IV, Alexandre Passos, Sameer Singh, Ming-Wei Chang

* v1.0 

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Faster Neural Network Training with Data Echoing


Jul 12, 2019
Dami Choi, Alexandre Passos, Christopher J. Shallue, George E. Dahl


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TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning


Feb 27, 2019
Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai

* Proc. of the 2nd SysML Conference, 2019 

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Scikit-learn: Machine Learning in Python


Jun 05, 2018
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Andreas Müller, Joel Nothman, Gilles Louppe, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Édouard Duchesnay

* Journal of Machine Learning Research (2011) 
* Update authors list and URLs 

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Large scale distributed neural network training through online distillation


Apr 09, 2018
Rohan Anil, Gabriel Pereyra, Alexandre Passos, Robert Ormandi, George E. Dahl, Geoffrey E. Hinton


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Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space


Apr 24, 2015
Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum

* In Conference on Empirical Methods in Natural Language Processing, 2014 

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Learning Soft Linear Constraints with Application to Citation Field Extraction


Oct 17, 2014
Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum

* appears in Proc. the 52nd Annual Meeting of the Association for Computational Linguistics (ACL2014) 

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Lexicon Infused Phrase Embeddings for Named Entity Resolution


Apr 22, 2014
Alexandre Passos, Vineet Kumar, Andrew McCallum

* Accepted in CoNLL 2014 

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Flexible Modeling of Latent Task Structures in Multitask Learning


Jun 27, 2012
Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daume III

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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