19 citations · 41 across the 7 of their papers we have counts for
3 papers · 1 filter
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning
Lyes Khacef, Vincent Gripon, Benoit Miramond
Few-shot classification is a challenge in machine learning where the goal is to train a classifier using a very limited number of labeled examples. This scenario is likely to occur…
Improving Self-Organizing Maps with Unsupervised Feature Extraction
Lyes Khacef, Laurent Rodriguez, Benoit Miramond
The Self-Organizing Map (SOM) is a brain-inspired neural model that is very promising for unsupervised learning, especially in embedded applications. However, it is unable to learn…
Brain-inspired self-organization with cellular neuromorphic computing for multimodal unsupervised learning
Lyes Khacef, Laurent Rodriguez, Benoit Miramond
Cortical plasticity is one of the main features that enable our ability to learn and adapt in our environment. Indeed, the cerebral cortex self-organizes itself through structural…