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ORCIDAlexandre Tachard Passos
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2020 – today
- 2023
[j3]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:
Scaling Up Models and Data with t5x and seqio. J. Mach. Learn. Res. 24: 377:1-377:8 (2023)- [c11]Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai:
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models. ICML 2023: 35120-35136 - [i13]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.:
PaLM 2 Technical Report. CoRR abs/2305.10403 (2023) - 2022
- [c10]Robert L. Logan IV, Alexandre Passos, Sameer Singh, Ming-Wei Chang:
FRUIT: Faithfully Reflecting Updated Information in Text. NAACL-HLT 2022: 3670-3686 - [i12]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:
Scaling Up Models and Data with t5x and seqio. CoRR abs/2203.17189 (2022) - [i11]Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Passos, Sumit Sanghai:
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models. CoRR abs/2210.15458 (2022) - 2021
- [i10]Robert L. Logan IV, Alexandre Passos, Sameer Singh, Ming-Wei Chang:
FRUIT: Faithfully Reflecting Updated Information in Text. CoRR abs/2112.08634 (2021)
2010 – 2019
- 2019
- [j2]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:
Report on the First HIPstIR Workshop on the Future of Information Retrieval. SIGIR Forum 53(2): 62-75 (2019) - [c9]Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai:
TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning. SysML 2019 - [i9]Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai:
TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning. CoRR abs/1903.01855 (2019) - [i8]Dami Choi, Alexandre Passos, Christopher J. Shallue, George E. Dahl:
Faster Neural Network Training with Data Echoing. CoRR abs/1907.05550 (2019) - [i7]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:
Report on the First HIPstIR Workshop on the Future of Information Retrieval. CoRR abs/1912.09910 (2019) - 2018
- [c8]Rohan Anil, Gabriel Pereyra, Alexandre Passos, Róbert Ormándi, George E. Dahl, Geoffrey E. Hinton:
Large scale distributed neural network training through online distillation. ICLR (Poster) 2018 - [i6]Rohan Anil, Gabriel Pereyra, Alexandre Passos, Róbert Ormándi, George E. Dahl, Geoffrey E. Hinton:
Large scale distributed neural network training through online distillation. CoRR abs/1804.03235 (2018) - 2015
- [i5]Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum:
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. CoRR abs/1504.06654 (2015) - 2014
- [c7]Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum:
Learning Soft Linear Constraints with Application to Citation Field Extraction. ACL (1) 2014: 593-602 - [c6]Alexandre Passos, Vineet Kumar, Andrew McCallum:
Lexicon Infused Phrase Embeddings for Named Entity Resolution. CoNLL 2014: 78-86 - [c5]Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum:
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. EMNLP 2014: 1059-1069 - [c4]David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum:
Message Passing for Soft Constraint Dual Decomposition. UAI 2014: 62-71 - [i4]Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum:
Learning Soft Linear Constraints with Application to Citation Field Extraction. CoRR abs/1403.1349 (2014) - [i3]Alexandre Passos, Vineet Kumar, Andrew McCallum:
Lexicon Infused Phrase Embeddings for Named Entity Resolution. CoRR abs/1404.5367 (2014) - 2013
- [b1]Alexandre Passos:
Algoritmos combinatórios e de programação linear para inferência em processamento de linguagem natural. University of Campinas, Brazil, 2013 - [i2]Sameer Singh, Limin Yao, David Belanger, Ari Kobren, Sam Anzaroot, Mike Wick, Alexandre Passos, Harshal Pandya, Jinho D. Choi, Brian Martin, Andrew McCallum:
Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013. TAC 2013 - 2012
- [c3]Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé III:
Flexible Modeling of Latent Task Structures in Multitask Learning. ICML 2012 - [c2]David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum:
MAP Inference in Chains using Column Generation. NIPS 2012: 1853-1861 - [i1]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:
Scikit-learn: Machine Learning in Python. CoRR abs/1201.0490 (2012) - 2011
- [j1]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:
Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 12: 2825-2830 (2011)
2000 – 2009
- 2008
- [c1]Pedro Kröger, Alexandre Passos, Marcos Sampaio:
Rameau: a System for Automatic harmonic Analysis. ICMC 2008
Coauthor Index
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