Alexandre Tachard Passos

According to our database, Alexandre Tachard Passos authored at least 19 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Scaling Up Models and Data with t5x and seqio.

Adam Roberts, Hyung Won Chung, Gaurav Mishra, Anselm Levskaya, 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, Kehang Han, Michelle Casbon, 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

J. Mach. Learn. Res., 2023

PaLM 2 Technical Report.

Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.

CoRR, 2023

Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models.

Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai

Proceedings of the International Conference on Machine Learning, 2023

2022

Scaling Up Models and Data with t5x and 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

CoRR, 2022

FRUIT: Faithfully Reflecting Updated Information in Text.

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

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2019

Report on the First HIPstIR Workshop on the Future of Information Retrieval.

Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jordan Ramsdell, Adam Roegiest, David Smith, Alessandro Sordoni

SIGIR Forum, 2019

Faster Neural Network Training with Data Echoing.

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

CoRR, 2019

TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning.

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

Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019

2018

Large scale distributed neural network training through online distillation.

Rohan Anil, Gabriel Pereyra, Alexandre Passos, Róbert Ormándi, George E. Dahl, Geoffrey E. Hinton

Proceedings of the 6th International Conference on Learning Representations, 2018

2014

Message Passing for Soft Constraint Dual Decomposition.

David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

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

Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Lexicon Infused Phrase Embeddings for Named Entity Resolution.

Alexandre Passos, Vineet Kumar, Andrew McCallum

Proceedings of the Eighteenth Conference on Computational Natural Language Learning, 2014

Learning Soft Linear Constraints with Application to Citation Field Extraction.

Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014

2013

Algoritmos combinatórios e de programação linear para inferência em processamento de linguagem natural.

Alexandre Passos

PhD thesis, 2013

Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013.

Sameer Singh, Limin Yao, David Belanger, Ari Kobren, Sam Anzaroot, Mike Wick, Alexandre Passos, Harshal Pandya, Jinho D. Choi, Brian Martin, Andrew McCallum

Proceedings of the Sixth Text Analysis Conference, 2013

2012

MAP Inference in Chains using Column Generation.

David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Flexible Modeling of Latent Task Structures in Multitask Learning.

Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé III

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Scikit-learn: Machine Learning in Python.

Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay

J. Mach. Learn. Res., 2011

2008

Rameau: a System for Automatic harmonic Analysis.

Pedro Kröger, Alexandre Passos, Marcos Sampaio

Proceedings of the 2008 International Computer Music Conference, 2008