Applying machine learning science to Facebook products
Connecting people with the content and stories they care about most.
Machine learning and Applied Machine Learning is essential to Facebook. It helps people discover new content and connect with the stories they care the most about. Our machine learning and applied machine learning researchers and engineers develop machine learning algorithms that rank feeds, ads and search results, and create new text understanding algorithms that keep spam and misleading content at bay. New computer vision algorithms can “read” images and videos to the blind and display over 2 billion translated stories every day, speech recognition systems automatically caption the videos that play in your news feed, and we create new magical visual experiences such as turning panorama photos into fully interactive 360 photos.
“We seek to advance the state of the art in machine learning for maximum impact, and our efforts form the glue between science and research and Facebook experiences.” Joaquin Quinonero Candela, Director of Applied Machine Learning
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Latest PublicationsAll Publications
ICPR - January 15, 2021
Sarah Bechtle, Artem Molchanov, Yevgen Chebotar, Edward Grefenstette, Ludovic Righetti, Gaurav S. Sukhatme, Franziska Meier
NeurIPS - December 16, 2020
Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti
NeurIPS - December 15, 2020
Stéphane d'Ascoli, Levent Sagun, Giulio Biroli
COLING - December 8, 2020
Best Practices for Data-Efficient Modeling in NLG: How to Train Production-Ready Neural Models with Less Data
Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Peyman Heidari, Hakan Inan, Shashank Jain, Anuj Kumar, Shawn Mei, Karthik Mohan, Michael White
Latest NewsAll News
1:01 | August 31, 2020
1:31 | August 31, 2020
1:30 | August 24, 2020
2:00 | August 21, 2020
Open Research AwardsView All Open Research Awards
With this RFP, we hope to deepen our ties to the academic research community by seeking out innovative ideas and applications of Bayesian optimization that further advance the field. We are committed to open source and will help awardees make the products of this RFP available to the public as part of BoTorch.