241 citations · 502 across the 15 of their papers we have counts for
16 papers
Adaptive Pruning with Module Robustness Sensitivity: Balancing Compression and Robustness
Lincen Bai, Hedi Tabia, Raúl Santos-Rodríguez
Neural network pruning has traditionally focused on weight-based criteria to achieve model compression, frequently overlooking the crucial balance between adversarial robustness an…
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network
Haozhe Sun, Isabelle Guyon, Felix Mohr +1
It has become mainstream in computer vision and other machine learning domains to reuse backbone networks pre-trained on large datasets as preprocessors. Typically, the last layer…
Efficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Search
Alexandre Heuillet, Ahmad Nasser, Hichem Arioui +1
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectur…
Kernel function impact on convolutional neural networks
M. Amine Mahmoudi, Aladine Chetouani, Fatma Boufera +1
This paper investigates the usage of kernel functions at the different layers in a convolutional neural network. We carry out extensive studies of their impact on convolutional, po…
Alphazzle: Jigsaw Puzzle Solver with Deep Monte-Carlo Tree Search
Marie-Morgane Paumard, Hedi Tabia, David Picard
Solving jigsaw puzzles requires to grasp the visual features of a sequence of patches and to explore efficiently a solution space that grows exponentially with the sequence length.…
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese Networks
Alexandre Heuillet, Hedi Tabia, Hichem Arioui
Siamese networks are one of the most trending methods to achieve self-supervised visual representation learning (SSL). Since hand labeling is costly, SSL can play a crucial part by…