Search Results for author: Greg Corrado

Found 15 papers, 7 papers with code

AI system for fetal ultrasound in low-resource settings

no code implementations18 Mar 2022 Ryan G. Gomes, Bellington Vwalika, Chace Lee, Angelica Willis, Marcin Sieniek, Joan T. Price, Christina Chen, Margaret P. Kasaro, James A. Taylor, Elizabeth M. Stringer, Scott Mayer McKinney, Ntazana Sindano, George E. Dahl, William Goodnight III, Justin Gilmer, Benjamin H. Chi, Charles Lau, Terry Spitz, T Saensuksopa, Kris Liu, Jonny Wong, Rory Pilgrim, Akib Uddin, Greg Corrado, Lily Peng, Katherine Chou, Daniel Tse, Jeffrey S. A. Stringer, Shravya Shetty

Using a simplified sweep protocol with real-time AI feedback on sweep quality, we have demonstrated the generalization of model performance to minimally trained novice ultrasound operators using low cost ultrasound devices with on-device AI integration.

Detecting Deficient Coverage in Colonoscopies

no code implementations23 Jan 2020 Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin

Our coverage algorithm is the first such algorithm to be evaluated in a large-scale way; while our depth estimation technique is the first calibration-free unsupervised method applied to colonoscopies.

Depth Estimation

Explaining an increase in predicted risk for clinical alerts

no code implementations10 Jul 2019 Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt

We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estimates given an input at each time step.

The Algorithmic Automation Problem: Prediction, Triage, and Human Effort

no code implementations28 Mar 2019 Maithra Raghu, Katy Blumer, Greg Corrado, Jon Kleinberg, Ziad Obermeyer, Sendhil Mullainathan

In a wide array of areas, algorithms are matching and surpassing the performance of human experts, leading to consideration of the roles of human judgment and algorithmic prediction in these domains.

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

4 code implementations TACL 2017 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

In addition to improving the translation quality of language pairs that the model was trained with, our models can also learn to perform implicit bridging between language pairs never seen explicitly during training, showing that transfer learning and zero-shot translation is possible for neural translation.

Machine Translation Transfer Learning +1

Wide & Deep Learning for Recommender Systems

32 code implementations24 Jun 2016 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

Memorization of feature interactions through a wide set of cross-product feature transformations are effective and interpretable, while generalization requires more feature engineering effort.

Click-Through Rate Prediction Feature Engineering +2

Smart Reply: Automated Response Suggestion for Email

no code implementations15 Jun 2016 Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, Laszlo Lukacs, Marina Ganea, Peter Young, Vivek Ramavajjala

In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply.

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

2 code implementations9 Oct 2014 Stephan Gouws, Yoshua Bengio, Greg Corrado

We introduce BilBOWA (Bilingual Bag-of-Words without Alignments), a simple and computationally-efficient model for learning bilingual distributed representations of words which can scale to large monolingual datasets and does not require word-aligned parallel training data.

Cross-Lingual Document Classification Document Classification +2

Distributed Representations of Words and Phrases and their Compositionality

42 code implementations NeurIPS 2013 Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean

Motivated by this example, we present a simple method for finding phrases in text, and show that learning good vector representations for millions of phrases is possible.

Efficient Estimation of Word Representations in Vector Space

71 code implementations16 Jan 2013 Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean

We propose two novel model architectures for computing continuous vector representations of words from very large data sets.

Word Similarity

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