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ORCIDGhouthi Boukli Hacene
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Books and Theses
- 2019
[b1]Ghouthi Boukli Hacene:
Processing and learning deep neural networks on chip. (Traitement et apprentissage des réseaux de neurones profonds sur puce). IMT Atlantique, France, 2019
Journal Articles
- 2021
- [j2]Pierre-Emmanuel Novac
, Ghouthi Boukli Hacene, Alain Pegatoquet, Benoît Miramond, Vincent Gripon:
Quantization and Deployment of Deep Neural Networks on Microcontrollers. Sensors 21(9): 2984 (2021) - 2019
- [j1]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories. J. Signal Process. Syst. 91(9): 1063-1073 (2019)
Conference and Workshop Papers
- 2024
- [c14]Luca Zampierin, Ghouthi Boukli Hacene, Bac Nguyen, Mirco Ravanelli:
Skill: Similarity-Aware Knowledge Distillation for Speech Self-Supervised Learning. ICASSP Workshops 2024: 675-679 - [c13]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. ISCAS 2024: 1-5 - 2023
- [c12]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Giulia Lioi, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux, Ghouthi Boukli Hacene, Javier Alonso García:
A Statistical Model for Predicting Generalization in Few-Shot Classification. EUSIPCO 2023: 1260-1264 - 2021
- [c11]Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Yasser Idris, Davis Sawyer, MohammadHossein AskariHemmat, Ghouthi Boukli Hacene:
Deeplite NeutrinoTM: A BlackBox Framework for Constrained Deep Learning Model Optimization. AAAI 2021: 15166-15174 - 2020
- [c10]Carlos Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep Geometric Knowledge Distillation with Graphs. ICASSP 2020: 8484-8488 - [c9]Ghouthi Boukli Hacene, Carlos Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. ICPR 2020: 4054-4061 - [c8]Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio:
Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. NEWCAS 2020: 206-209 - 2019
- [c7]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. DSW 2019: 160-164 - [c6]Ghouthi Boukli Hacene, François Leduc-Primeau, Amal Ben Soussia, Vincent Gripon, François Gagnon:
Training Modern Deep Neural Networks for Memory-Fault Robustness. ISCAS 2019: 1-5 - [c5]Ghouthi B. Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Efficient Hardware Implementation of Incremental Learning and Inference on Chip. NEWCAS 2019: 1-4 - 2018
- [c4]Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe, Franck Vermet:
Improving Accuracy of Nonparametric Transfer Learning Via Vector Segmentation. ICASSP 2018: 2966-2970 - 2017
- [c3]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Incremental learning on chip. GlobalSIP 2017: 789-792 - [c2]Max Raphael Sobroza Marques, Ghouthi Boukli Hacene, Carlos Eduardo Rosar Kós Lassance, Pierre-Henri Horrein:
Large-Scale Memory of Sequences Using Binary Sparse Neural Networks on GPU. HPCS 2017: 553-559 - [c1]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Budget restricted incremental learning with pre-trained convolutional neural networks and binary associative memories. SiPS 2017: 1-6
Informal and Other Publications
- 2024
- [i20]Reda Bensaid, Vincent Gripon, François Leduc-Primeau, Lukas Mauch, Ghouthi Boukli Hacene, Fabien Cardinaux:
A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models. CoRR abs/2401.11311 (2024) - [i19]Luca Zampierin, Ghouthi Boukli Hacene, Bac Nguyen, Mirco Ravanelli:
SKILL: Similarity-aware Knowledge distILLation for Speech Self-Supervised Learning. CoRR abs/2402.16830 (2024) - [i18]Yassir Bendou, Giulia Lioi, Bastien Pasdeloup, Lukas Mauch, Ghouthi Boukli Hacene, Fabien Cardinaux, Vincent Gripon:
LLM meets Vision-Language Models for Zero-Shot One-Class Classification. CoRR abs/2404.00675 (2024) - 2023
- [i17]Hugo Tessier, Ghouthi Boukli Hacene, Vincent Gripon:
ThinResNet: A New Baseline for Structured Convolutional Networks Pruning. CoRR abs/2309.12854 (2023) - [i16]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Giulia Lioi, Lukas Mauch, Fabien Cardinaux, Ghouthi Boukli Hacene:
Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning. CoRR abs/2311.14544 (2023) - 2022
- [i15]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux, Ghouthi Boukli Hacene, Javier Alonso García:
A Statistical Model for Predicting Generalization in Few-Shot Classification. CoRR abs/2212.06461 (2022) - 2021
- [i14]Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Yasser Idris, Davis Sawyer, MohammadHossein AskariHemmat, Ghouthi Boukli Hacene:
Deeplite Neutrino: An End-to-End Framework for Constrained Deep Learning Model Optimization. CoRR abs/2101.04073 (2021) - [i13]Ghouthi Boukli Hacene, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux:
DNN Quantization with Attention. CoRR abs/2103.13322 (2021) - [i12]Pierre-Emmanuel Novac, Ghouthi Boukli Hacene, Alain Pegatoquet, Benoît Miramond, Vincent Gripon:
Quantization and Deployment of Deep Neural Networks on Microcontrollers. CoRR abs/2105.13331 (2021) - 2020
- [i11]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. CoRR abs/2002.03090 (2020) - [i10]Guillaume Coiffier, Ghouthi Boukli Hacene, Vincent Gripon:
ThriftyNets : Convolutional Neural Networks with Tiny Parameter Budget. CoRR abs/2007.10106 (2020) - [i9]Vincent Gripon, Carlos Lassance, Ghouthi Boukli Hacene:
DecisiveNets: Training Deep Associative Memories to Solve Complex Machine Learning Problems. CoRR abs/2012.01509 (2020) - 2019
- [i8]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. CoRR abs/1905.00301 (2019) - [i7]Ghouthi Boukli Hacene, Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. CoRR abs/1905.12300 (2019) - [i6]Carlos Eduardo Rosar Kós Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep geometric knowledge distillation with graphs. CoRR abs/1911.03080 (2019) - [i5]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Efficient Hardware Implementation of Incremental Learning and Inference on Chip. CoRR abs/1911.07847 (2019) - [i4]Ghouthi Boukli Hacene, François Leduc-Primeau, Amal Ben Soussia, Vincent Gripon, François Gagnon:
Training Modern Deep Neural Networks for Memory-Fault Robustness. CoRR abs/1911.10287 (2019) - 2018
- [i3]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Transfer Incremental Learning using Data Augmentation. CoRR abs/1810.02020 (2018) - [i2]Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio:
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks. CoRR abs/1812.11337 (2018) - 2017
- [i1]Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe, Franck Vermet:
Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation. CoRR abs/1710.08637 (2017)
Coauthor Index
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