Fadhel Ayed
Fadhel Ayed
Department of Statistics, University of Oxford
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
Large Language Models for Telecom: Forthcoming Impact on the Industry
A Maatouk, N Piovesan, F Ayed, A De Domenico, M Debbah
arXiv preprint arXiv:2308.06013, 2023
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
F Ayed, J Lee, F Caron
International Conference on Machine Learning 97, 395-404, 2019
TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
A Maatouk, F Ayed, N Piovesan, A De Domenico, M Debbah, ZQ Luo
arXiv preprint arXiv:2310.15051, 2023
On consistent and rate optimal estimation of the missing mass
M Battiston, F Ayed, F Camerlenghi, S Favaro
Annales de l’institut Henri Poincare (B) Probability and Statistics 1 (3), 2020
Anomaly detection at scale: The case for deep distributional time series models
F Ayed, L Stella, T Januschowski, J Gasthaus
International Conference on Service-Oriented Computing, 97-109, 2020
Regularization in ResNet with Stochastic Depth
S Hayou, F Ayed
Advances in Neural Information Processing Systems 34, 15464-15474, 2021
A Good-Turing estimator for feature allocation models
F Ayed, M Battiston, F Camerlenghi, S Favaro
Electronic Journal of Statistics 13 (2), 3775-3804, 2019
Nonnegative Bayesian nonparametric factor models with completely random measures
F Ayed, F Caron
Statistics and Computing 31, 1-24, 2021
Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks
F Ayed, A De Domenico, A Garcia-Rodriguez, D López-Pérez
IEEE Communications Magazine 61 (6), 104-110, 2023
Data pruning and neural scaling laws: fundamental limitations of score-based algorithms
F Ayed, S Hayou
Transactions on Machine Learning Research 2023 (arXiv preprint arXiv:2302.06960), 2023
Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility
H Lee, F Ayed, P Jung, J Lee, H Yang, F Caron
Journal of Machine Learning Research 24 (289), 1-78, 2023
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning
F Caron, F Ayed, P Jung, H Lee, J Lee, H Yang
arXiv preprint arXiv:2302.01002, 2023
The normal-generalised gamma-Pareto process: a novel pure-jump Lévy process with flexible tail and jump-activity properties
F Ayed, J Lee, F Caron
Bayesian Analysis 19 (1), 123-152, 2024
Consistent estimation of small masses in feature sampling
F Ayed, M Battiston, F Camerlenghi, S Favaro
Journal of Machine Learning Research 22 (6), 1-28, 2021
An information theoretic approach to post randomization methods under differential privacy
F Ayed, M Battiston, F Camerlenghi
Statistics and Computing 30 (5), 1347-1361, 2020
Telecom Language Models: Must They Be Large?
N Piovesan, A De Domenico, F Ayed
arXiv preprint arXiv:2403.04666, 2024
The curse of (non) convexity: The case of an Optimization-Inspired Data Pruning algorithm
F Ayed, S Hayou
I Can't Believe It's Not Better Workshop: Understanding Deep Learning …, 2022
A Mathematical Framework for the Evaluation of System Expected Utility Not Satis-fied Under Periodic Demand
A Maatouk, F Ayed, W Li, H Bao, D Miao, K Lin, X Chen, E Zio
the 32nd European Safety and Reliability Conference (ESREL 2022).[Online …, 2022
Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications
AL Bornea, F Ayed, A De Domenico, N Piovesan, A Maatouk
arXiv preprint arXiv:2404.15939, 2024
A Framework for the Evaluation of Network Reliability Under Periodic Demand
A Maatouk, F Ayed, S Biao, W Li, H Bao, E Zio
IEEE/ACM Transactions on Networking, 2024
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