Ghouthi Boukli Hacene

verfied profile

Featured Co-authors

Yoshua Bengio
393 publications
Jian Tang
110 publications
Vincent Gripon
58 publications
Antonio Ortega
32 publications
Carlos Lassance
19 publications
Andreas Moshovos
16 publications
Anush Sankaran
16 publications
Stefan Uhlich
14 publications
Milos Nikolic
13 publications
François Leduc-Primeau
12 publications
Myriam Bontonou
9 publications

∙ 05/27/2021

Quantization and Deployment of Deep Neural Networks on Microcontrollers

Embedding Artificial Intelligence onto low-power devices is a challengin...

Pierre-Emmanuel Novac, et al. ∙

∙ 03/24/2021

DNN Quantization with Attention

Low-bit quantization of network weights and activations can drastically ...

Ghouthi Boukli Hacene, et al. ∙

∙ 01/11/2021

Deeplite Neutrino: An End-to-End Framework for Constrained Deep Learning Model Optimization

Designing deep learning-based solutions is becoming a race for training ...

Anush Sankaran, et al. ∙

∙ 12/02/2020

DecisiveNets: Training Deep Associative Memories to Solve Complex Machine Learning Problems

Learning deep representations to solve complex machine learning tasks ha...

Vincent Gripon, et al. ∙

∙ 07/20/2020

ThriftyNets : Convolutional Neural Networks with Tiny Parameter Budget

Typical deep convolutional architectures present an increasing number of...

Guillaume Coiffier, et al. ∙

∙ 02/08/2020

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization

Neural networks have demonstrably achieved state-of-the art accuracy usi...

Milos Nikolic, et al. ∙

∙ 11/23/2019

Training Modern Deep Neural Networks for Memory-Fault Robustness

Because deep neural networks (DNNs) rely on a large number of parameters...

Ghouthi Boukli Hacene, et al. ∙

∙ 11/18/2019

Efficient Hardware Implementation of Incremental Learning and Inference on Chip

In this paper, we tackle the problem of incrementally learning a classif...

Ghouthi Boukli Hacene, et al. ∙

∙ 11/08/2019

Deep geometric knowledge distillation with graphs

In most cases deep learning architectures are trained disregarding the a...

Carlos Lassance, et al. ∙

∙ 05/29/2019

Attention Based Pruning for Shift Networks

In many application domains such as computer vision, Convolutional Layer...

Ghouthi Boukli Hacene, et al. ∙

∙ 05/01/2019

Introducing Graph Smoothness Loss for Training Deep Learning Architectures

We introduce a novel loss function for training deep learning architectu...

Myriam Bontonou, et al. ∙

∙ 12/29/2018

Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are state-of-the-art in numerous co...

Ghouthi Boukli Hacene, et al. ∙

∙ 10/04/2018

Transfer Incremental Learning using Data Augmentation

Deep learning-based methods have reached state of the art performances, ...

Ghouthi Boukli Hacene, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world