Fadhel Ayed

According to our database1, Fadhel Ayed authored at least 21 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Large Language Models for Telecom: Forthcoming Impact on the Industry.
IEEE Commun. Mag., January, 2025

2024
A Framework for the Evaluation of Network Reliability Under Periodic Demand.
IEEE/ACM Trans. Netw., June, 2024

Hermes: A Large Language Model Framework on the Journey to Autonomous Networks.
CoRR, 2024

Pay Attention to What Matters.
CoRR, 2024

Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications.
CoRR, 2024

Telecom Language Models: Must They Be Large?
Proceedings of the 35th IEEE International Symposium on Personal, 2024

2023
Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks.
IEEE Commun. Mag., June, 2023

Data pruning and neural scaling laws: fundamental limitations of score-based algorithms.
Trans. Mach. Learn. Res., 2023

Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility.
J. Mach. Learn. Res., 2023

FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments.
CoRR, 2023

TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge.
CoRR, 2023

Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning.
CoRR, 2023

An Optimization Framework for Anomaly Detection Scores Refinement with Side Information.
Proceedings of the IEEE Global Communications Conference, 2023

2021
Nonnegative Bayesian nonparametric factor models with completely random measures.
Stat. Comput., 2021

Consistent estimation of small masses in feature sampling.
J. Mach. Learn. Res., 2021

Regularization in ResNet with Stochastic Depth.
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.
Stat. Comput., 2020

A Bayesian Nonparametric Approach to Differentially Private Data.
Proceedings of the Privacy in Statistical Databases, 2020

Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models.
Proceedings of the Service-Oriented Computing - ICSOC 2020 Workshops, 2020

2019
Nonnegative Bayesian nonparametric factor models with completely random measures for community detection.
CoRR, 2019

Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior.
Proceedings of the 36th International Conference on Machine Learning, 2019


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