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
Human Interpretability Workshop at ICML - April 9, 2021
Vivek Miglani, Bilal Alsallakh, Narine Kokhlikyan, Orion Reblitz-Richardson
ICASSP - April 8, 2021
Panagiotis Tzirakis, Anurag Kumar, Jacob Donley
ICSE - March 5, 2021
John Ahlgren, Maria Eugenia Berezin, Kinga Bojarczuk, Elena Dulskyte, Inna Dvortsova, Johann George, Natalija Gucevska, Mark Harman, Maria Lomeli, Erik Meijer, Silvia Sapora, Justin Spahr-Summers
JMLR - February 11, 2021
Carlos A. Gómez-Uribe, Brian Karrer
Latest NewsAll News
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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.