Large machine learning models, or so-called foundation models, aim to se...
The geometric median of a tuple of vectors is the vector that minimizes ...
Today's large-scale algorithms have become immensely influential, as the...
Byzantine Machine Learning (ML) systems are nowadays vulnerable for they...
We address the problem of Byzantine collaborative learning: a set of n
n...
Generative adversarial networks (GANs) are pairs of artificial neural
ne...
Momentum is a variant of gradient descent that has been proposed for its...
Machine Learning (ML) solutions are nowadays distributed and are prone t...
Modern machine learning is distributed and the work of several machines ...
The size of the datasets available today leads to distribute Machine Lea...
The loss of a few neurons in a brain often does not result in a visible ...
We address the problem of correcting group discriminations within a scor...
We show that when a third party, the adversary, steps into the two-party...
Asynchronous distributed machine learning solutions have proven very
eff...
While machine learning is going through an era of celebrated success,
co...
A standard belief on emerging collective behavior is that it emerges fro...
With the development of neural networks based machine learning and their...
We view a neural network as a distributed system of which neurons can fa...
In reinforcement learning, agents learn by performing actions and observ...
The growth of data, the need for scalability and the complexity of model...