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Greg Corrado

Greg Corrado is a senior research scientist interested in biological neuroscience, artificial intelligence, and scalable machine learning. He has published in fields ranging across behavioral economics, neuromorphic device physics, systems neuroscience, and deep learning. At Google he has worked for some time on brain inspired computing, and most recently has served as one of the founding members and the co-technical lead of Google's large scale deep neural networks project.

Google Publications

Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy

Dale Webster, Ehsan Rahimy, Greg Corrado, Jonathan Krause, Kasumi Widner, Lily Peng, Peter Karth, Varun Gulshan

Ophthalmology (2018)
Detecting Cancer Metastases on Gigapixel Pathology Images

Yun Liu, Krishna Kumar Gadepalli, Mohammad Norouzi, George Dahl, Timo Kohlberger, Subhashini Venugopalan, Aleksey S Boyko, Aleksei Timofeev, Philip Q Nelson, Greg Corrado, Jason Hipp, Lily Peng, Martin Stumpe

MICCAI (2017)
Predicting Cardiovascular Risk Factors in Retinal Fundus Photographs using Deep Learning

Ryan Poplin, Avinash Vaidyanathan Varadarajan, Katy Blumer, Yun Liu, Mike McConnell, Greg Corrado, Lily Peng, Dale Webster

Arxiv (2017)
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean

Google (2016)
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean

CoRR, vol. abs/1609.08144 (2016)
Smart Reply: Automated Response Suggestion for Email

Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufman, Balint Miklos, Greg Corrado, Andrew Tomkins, Laszlo Lukacs, Marina Ganea, Peter Young, Vivek Ramavajjala

Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (2016).
Wide & Deep Learning for Recommender Systems

Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah

arXiv:1606.07792 (2016)
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

Stephan Gouws, Yoshua Bengio, Greg Corrado

Proceedings of the 32nd International Conference on Machine Learning (2015)
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

tensorflow.org (2015)
Zero-Shot Learning by Convex Combination of Semantic Embeddings

Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean

International Conference on Learning Representations (2014)
DeViSE: A Deep Visual-Semantic Embedding Model

Andrea Frome, Greg Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc’Aurelio Ranzato, Tomas Mikolov

Neural Information Processing Systems (NIPS) (2013)
Distributed Representations of Words and Phrases and their Compositionality

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean

Neural and Information Processing System (NIPS) (2013)
Efficient Estimation of Word Representations in Vector Space

Tomas Mikolov, Kai Chen, Greg S. Corrado, Jeffrey Dean

International Conference on Learning Representations (2013)
Building high-level features using large scale unsupervised learning

Quoc Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg Corrado, Jeff Dean, Andrew Ng

International Conference in Machine Learning (2012)
Large Scale Distributed Deep Networks

Jeffrey Dean, Greg S. Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Andrew Y. Ng

NIPS (2012)
Three Controversial Hypotheses Concerning Computation in the Primate Cortex

Thomas Dean, Greg Corrado, Jonathon Shlens

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, AAAI Press (2012)
Recursive Sparse Spatiotemporal Coding

Thomas Dean, Greg Corrado, Richard Washington

Proceedings of the Fifth IEEE International Workshop on Multimedia Information Processing and Retrieval, IEEE Computer Society (2009)

Previous Publications

Sparse Spatiotemporal Coding for Activity Recognition

Thomas Dean, Greg Corrado, Rich Washington

Brown University (2010)