Unit
Information, Learning & Physics Laboratory (STI/SB)
LaboratoryRelated publications (32)
Theory of representation learning in cortical neural networks
Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...
EPFL2016Adaptive data augmentation for image classification
Pascal Frossard, Alhussein Fawzi
Data augmentation is the process of generating samples by transforming training data, with the target of improving the accuracy and robustness of classifiers. In this paper, we propose a new automatic and adaptive algorithm for choosing the transformations ...
IEEE2016