68 citations · 159 across the 37 of their papers we have counts for
5 papers · 1 filter
Simplex Autoencoders
Aymene Mohammed Bouayed, David Naccache
Synthetic data generation is increasingly important due to privacy concerns. While Autoencoder-based approaches have been widely used for this purpose, sampling from their latent s…
FedControl: When Control Theory Meets Federated Learning
Adnan Ben Mansour, Gaia Carenini, Alexandre Duplessis +1
To date, the most popular federated learning algorithms use coordinate-wise averaging of the model parameters. We depart from this approach by differentiating client contributions…
Noise-Resilient Ensemble Learning using Evidence Accumulation Clustering
Gaëlle Candel, David Naccache
Ensemble Learning methods combine multiple algorithms performing the same task to build a group with superior quality. These systems are well adapted to the distributed setup, wher…
Index -SNE: Tracking Dynamics of High-Dimensional Datasets with Coherent Embeddings
Gaëlle Candel, David Naccache
-SNE is an embedding method that the data science community has widely Two interesting characteristics of t-SNE are the structure preservation property and the answer to the cro…
Genealogical Population-Based Training for Hyperparameter Optimization
Antoine Scardigli, Paul Fournier, Matteo Vilucchio +1
HyperParameter Optimization (HPO) aims at finding the best HyperParameters (HPs) of learning models, such as neural networks, in the fastest and most efficient way possible. Most r…