Machine Learning

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

Latest Publications

All Publications

IEEE Spoken Language Technology Workshop (SLT) - January 9, 2022

Benchmarking LF-MMI, CTC and RNN-T Criteria for Streaming ASR

Xiaohui Zhang, Frank Zhang, Chunxi Liu, Kjell Schubert, Julian Chan, Pradyot Prakash, Jun Liu, Ching-Feng Yeh, Fuchun Peng, Yatharth Saraf, Geoffrey Zweig

ICLR - December 13, 2021

DINO: A Conditional Energy-based GAN for Domain Translation

Konstantinos Vougioukas, Stavros Petridis, Maja Pantic

Causal Discovery & Causality Workshop at NeurIPS - December 9, 2021

Linear unit-tests for invariance discovery

Benjamin Aubin, Agnieszka Słowik, Martin Arjovsky, Léon Bottou, David Lopez-Paz

Optimal Transport and Machine Learning (OTML) Workshop at NeurIPS - December 6, 2021

Input Convex Gradient Networks

Jack Richter-Powell, Jonathan Lorraine, Brandon Amos

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