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ORCIDFadhel Ayed
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2020 – today
- 2025
[j8]Ali Maatouk, Nicola Piovesan, Fadhel Ayed, Antonio De Domenico, Mérouane Debbah:
Large Language Models for Telecom: Forthcoming Impact on the Industry. IEEE Commun. Mag. 63(1): 62-68 (2025)- 2024
- [j7]Ali Maatouk
, Fadhel Ayed, Shi Biao, Wenjie Li, Harvey Bao, Enrico Zio:
A Framework for the Evaluation of Network Reliability Under Periodic Demand. IEEE/ACM Trans. Netw. 32(3): 2495-2510 (2024) - [c6]Nicola Piovesan, Antonio De Domenico, Fadhel Ayed:
Telecom Language Models: Must They Be Large? PIMRC 2024: 1-6 - [i17]Nicola Piovesan, Antonio De Domenico, Fadhel Ayed:
Telecom Language Models: Must They Be Large? CoRR abs/2403.04666 (2024) - [i16]Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico, Nicola Piovesan, Ali Maatouk:
Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications. CoRR abs/2404.15939 (2024) - [i15]Pedro Luiz Silva, Antonio De Domenico, Ali Maatouk, Fadhel Ayed:
Pay Attention to What Matters. CoRR abs/2409.19001 (2024) - [i14]Fadhel Ayed, Ali Maatouk, Nicola Piovesan, Antonio De Domenico, Mérouane Debbah, Zhi-Quan Luo:
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks. CoRR abs/2411.06490 (2024) - 2023
- [j6]Fadhel Ayed, Antonio De Domenico, Adrian García-Rodríguez, David López-Pérez:
Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks. IEEE Commun. Mag. 61(6): 104-110 (2023) - [j5]Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron:
Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility. J. Mach. Learn. Res. 24: 289:1-289:78 (2023) - [j4]Fadhel Ayed, Soufiane Hayou:
Data pruning and neural scaling laws: fundamental limitations of score-based algorithms. Trans. Mach. Learn. Res. 2023 (2023) - [c5]Ali Maatouk, Fadhel Ayed, Wenjie Li, Yu Wang, Hong Zhu, Jiantao Ye:
An Optimization Framework for Anomaly Detection Scores Refinement with Side Information. GLOBECOM 2023: 6043-6049 - [i13]Ali Maatouk, Fadhel Ayed, Shi Biao, Wenjie Li, Harvey Bao, Enrico Zio:
A Framework for the Evaluation of Network Reliability Under Periodic Demand. CoRR abs/2301.05589 (2023) - [i12]Fadhel Ayed, Antonio De Domenico, Adrian García-Rodríguez, David López-Pérez:
Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks. CoRR abs/2302.00623 (2023) - [i11]Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang:
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning. CoRR abs/2302.01002 (2023) - [i10]Fadhel Ayed, Soufiane Hayou:
Data pruning and neural scaling laws: fundamental limitations of score-based algorithms. CoRR abs/2302.06960 (2023) - [i9]Ali Maatouk, Fadhel Ayed, Wenjie Li, Yu Wang, Hong Zhu, Jiantao Ye:
An Optimization Framework For Anomaly Detection Scores Refinement With Side Information. CoRR abs/2304.11039 (2023) - [i8]Ali Maatouk, Nicola Piovesan, Fadhel Ayed, Antonio De Domenico, Mérouane Debbah:
Large Language Models for Telecom: Forthcoming Impact on the Industry. CoRR abs/2308.06013 (2023) - [i7]Ali Maatouk, Fadhel Ayed, Nicola Piovesan, Antonio De Domenico, Mérouane Debbah, Zhi-Quan Luo:
TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge. CoRR abs/2310.15051 (2023) - [i6]Mert Unsal, Ali Maatouk, Antonio De Domenico, Nicola Piovesan, Fadhel Ayed:
FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments. CoRR abs/2310.20457 (2023) - 2022
- [i5]Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, François Caron:
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility. CoRR abs/2205.08187 (2022) - 2021
- [j3]Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro:
Consistent estimation of small masses in feature sampling. J. Mach. Learn. Res. 22: 6:1-6:28 (2021) - [j2]Fadhel Ayed, François Caron:
Nonnegative Bayesian nonparametric factor models with completely random measures. Stat. Comput. 31(5): 63 (2021) - [c4]Soufiane Hayou, Fadhel Ayed:
Regularization in ResNet with Stochastic Depth. NeurIPS 2021: 15464-15474 - [i4]Soufiane Hayou, Fadhel Ayed:
Regularization in ResNet with Stochastic Depth. CoRR abs/2106.03091 (2021) - 2020
- [j1]Fadhel Ayed, Marco Battiston, Federico Camerlenghi:
An information theoretic approach to post randomization methods under differential privacy. Stat. Comput. 30(5): 1347-1361 (2020) - [c3]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. ICSOC Workshops 2020: 97-109 - [c2]Fadhel Ayed, Marco Battiston, Giuseppe Di Benedetto:
A Bayesian Nonparametric Approach to Differentially Private Data. PSD 2020: 32-48 - [i3]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. CoRR abs/2007.15541 (2020)
2010 – 2019
- 2019
- [c1]Fadhel Ayed, Juho Lee, Francois Caron:
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior. ICML 2019: 395-404 - [i2]Fadhel Ayed, Juho Lee, François Caron:
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior. CoRR abs/1902.04714 (2019) - [i1]Fadhel Ayed, François Caron:
Nonnegative Bayesian nonparametric factor models with completely random measures for community detection. CoRR abs/1902.10693 (2019)
Coauthor Index
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