Jimmy Lei Ba

E701498

Jimmy Lei Ba is a machine learning researcher known for influential contributions to deep learning optimization and normalization techniques, including the development of Layer Normalization.

All labels observed (1)

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Jimmy Lei Ba canonical 1

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Statements (41)

Predicate Object
instanceOf machine learning researcher ⓘ
person ⓘ
coAuthorOf Adam: A Method for Stochastic Optimization ⓘ
Layer Normalization ⓘ
contributedTo widespread adoption of Adam optimizer ⓘ
widespread adoption of Layer Normalization in deep learning models ⓘ
countryOfCitizenship Canada ⓘ
doctoralAdvisor Geoffrey Hinton ⓘ
educatedAt University of Toronto ⓘ
employer University of Toronto ⓘ
fieldOfWork deep learning ⓘ
machine learning ⓘ
normalization techniques in neural networks ⓘ
optimization in machine learning ⓘ
hasAcademicDegree PhD in Computer Science ⓘ
hasCitationImpactOn deep learning optimization practices ⓘ
normalization methods in neural networks ⓘ
hasCoAuthor Diederik P. Kingma ⓘ
Geoffrey Hinton ⓘ
Kyunghyun Cho ⓘ
Yoshua Bengio ⓘ
other deep learning researchers ⓘ
hasResearchInterest optimization algorithms for deep learning ⓘ
reinforcement learning ⓘ
representation learning ⓘ
scalable training of neural networks ⓘ
influencedBy Geoffrey Hinton ⓘ
knownFor Adam optimization algorithm ⓘ
linked to: Adam optimizer

Layer Normalization ⓘ
research on deep learning optimization ⓘ
research on neural network normalization ⓘ
languageWritten English ⓘ
notableStudent graduate students in machine learning ⓘ
notableWork Adam: A Method for Stochastic Optimization ⓘ
Layer Normalization ⓘ
occupation assistant professor ⓘ
publishesIn ICLR ⓘ
ICML ⓘ
NeurIPS ⓘ
machine learning conferences ⓘ
workLocation Toronto ⓘ

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Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

Layer Normalization → introducedBy → Jimmy Lei Ba ⓘ