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Quoc V. Le
Researcher at Google
Publications - 229
Citations - 127721
Quoc V. Le is an academic researcher from Google. The author has contributed to research in topics: Artificial neural network & Language model. The author has an hindex of 103, co-authored 217 publications receiving 101217 citations. Previous affiliations of Quoc V. Le include Northwestern University & Tel Aviv University.
Papers
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Proceedings ArticleDOI
Joint calibration of multiple sensors
Quoc V. Le,Andrew Y. Ng +1 more
TL;DR: This paper combines a number of ideas in the literature to derive a unified framework that jointly calibrates many sensors a large system, and shows that this method not only reduces calibration error, but also requires less human time.
Proceedings ArticleDOI
Scalable learning for object detection with GPU hardware
TL;DR: This paper describes an object detection system that is designed to scale gracefully to large data sets and leverages upward trends in computational power (as exemplified by Graphics Processing Unit (GPU) technology) and memory.
Posted Content
Carbon Emissions and Large Neural Network Training.
David A. Patterson,Joseph E. Gonzalez,Quoc V. Le,Chen Liang,Lluís-Miquel Munguía,Daniel Rothchild,David R. So,Maud Texier,Jeffrey Dean +8 more
TL;DR: In this article, the authors calculate the energy use and carbon footprint of several recent large models, including T5, Meena, GShard, Switch Transformer, and GPT-3, and refine earlier estimates for the neural architecture search that found evolved transformer.
Nonparametric Quantile Regression
TL;DR: In this article, a nonparametric version of a quantile estimator is presented, which can be obtained by solving a simple quadratic programming problem and provide uniform convergence statements and bounds on the quantile property of the estimator.
Posted Content
Latent Sequence Decompositions
TL;DR: The Latent Sequence Decomposition (LSD) framework as discussed by the authors decomposes sequences with variable lengthed output units as a function of both the input sequence and the output sequence.