Fadhel Ayed
Bayesian nonparametrics, Machine Learning
I am Fadhel Ayed, a doctoral researcher in Statistical Machine Learning at the University of Oxford, advised by Prof. François Caron.
My primary research subject is statistical machine learning with Bayesian Nonparametric methods and models. I have been working on two main lines of research: 1) Methodological and theoretical properties of clustering and feature allocation models, with applications to language and network modeling; 2) Privacy preservation and disclosure risk limitation.
Since September 2019, I have been working part-time with the AWS forecasting team at Amazon Research. I am developing models for anomaly detection at the intersection of Bayesian Machine Learning and Deep learning.
Publications
2019
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F. Ayed
,
F. Caron
,
Nonnegative Bayesian nonparametric factor models with completely random measures for community detection, 2019.
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F. Ayed
,
J. Lee
,
F. Caron
,
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior, 2019.
2018
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F. Ayed
,
M. Battiston
,
F. Camerlenghi
,
S. Favaro
,
Consistent estimation of the missing mass for feature models, 2018.
Project: bigbayes -
F. Ayed
,
M. Battiston
,
F. Camerlenghi
,
S. Favaro
,
On the consistent estimation of the missing mass, 2018.
Project: bigbayes -
F. Ayed
,
M. Battiston
,
F. Camerlenghi
,
S. Favaro
,
On the Good-Turing estimator for feature allocation models, 2018.
Project: bigbayes