Fadhel Ayed

According to our database, Fadhel Ayed authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Framework for the Evaluation of Network Reliability Under Periodic Demand.

Ali Maatouk, Fadhel Ayed, Shi Biao, Wenjie Li, Harvey Bao, Enrico Zio

IEEE/ACM Trans. Netw., June, 2024

Pay Attention to What Matters.

Pedro Luiz Silva, Antonio De Domenico, Ali Maatouk, Fadhel Ayed

CoRR, 2024

Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications.

Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico, Nicola Piovesan, Ali Maatouk

CoRR, 2024

Telecom Language Models: Must They Be Large?

Nicola Piovesan, Antonio De Domenico, Fadhel Ayed

CoRR, 2024

2023

Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks.

Fadhel Ayed, Antonio De Domenico, Adrian García-Rodríguez, David López-Pérez

IEEE Commun. Mag., June, 2023

Data pruning and neural scaling laws: fundamental limitations of score-based algorithms.

Fadhel Ayed, Soufiane Hayou

Trans. Mach. Learn. Res., 2023

Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility.

Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

J. Mach. Learn. Res., 2023

FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments.

Mert Unsal, Ali Maatouk, Antonio De Domenico, Nicola Piovesan, Fadhel Ayed

CoRR, 2023

TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge.

Ali Maatouk, Fadhel Ayed, Nicola Piovesan, Antonio De Domenico, Mérouane Debbah, Zhi-Quan Luo

CoRR, 2023

Large Language Models for Telecom: Forthcoming Impact on the Industry.

Ali Maatouk, Nicola Piovesan, Fadhel Ayed, Antonio De Domenico, Mérouane Debbah

CoRR, 2023

Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning.

Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang

CoRR, 2023

An Optimization Framework for Anomaly Detection Scores Refinement with Side Information.

Ali Maatouk, Fadhel Ayed, Wenjie Li, Yu Wang, Hong Zhu, Jiantao Ye

Proceedings of the IEEE Global Communications Conference, 2023

2021

Nonnegative Bayesian nonparametric factor models with completely random measures.

Fadhel Ayed, François Caron

Stat. Comput., 2021

Consistent estimation of small masses in feature sampling.

Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro

J. Mach. Learn. Res., 2021

Regularization in ResNet with Stochastic Depth.

Soufiane Hayou, Fadhel Ayed

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

An information theoretic approach to post randomization methods under differential privacy.

Fadhel Ayed, Marco Battiston, Federico Camerlenghi

Stat. Comput., 2020

A Bayesian Nonparametric Approach to Differentially Private Data.

Fadhel Ayed, Marco Battiston, Giuseppe Di Benedetto

Proceedings of the Privacy in Statistical Databases, 2020

Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models.

Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus

Proceedings of the Service-Oriented Computing - ICSOC 2020 Workshops, 2020

2019

Nonnegative Bayesian nonparametric factor models with completely random measures for community detection.

Fadhel Ayed, François Caron

CoRR, 2019

Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior.

Fadhel Ayed, Juho Lee, Francois Caron

Proceedings of the 36th International Conference on Machine Learning, 2019