59 citations · 134 across the 9 of their papers we have counts for
5 papers · 1 filter
Photonic Differential Privacy with Direct Feedback Alignment
Ruben Ohana, Hamlet J. Medina Ruiz, Julien Launay +4
Optical Processing Units (OPUs) -- low-power photonic chips dedicated to large scale random projections -- have been used in previous work to train deep neural networks using Direc…
Contrastive Embeddings for Neural Architectures
Daniel Hesslow, Iacopo Poli
The performance of algorithms for neural architecture search strongly depends on the parametrization of the search space. We use contrastive learning to identify networks across di…
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
Julien Launay, Iacopo Poli, Kilian Müller +5
The scaling hypothesis motivates the expansion of models past trillions of parameters as a path towards better performance. Recent significant developments, such as GPT-3, have bee…
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks
Julien Launay, Iacopo Poli, Kilian Müller +4
As neural networks grow larger and more complex and data-hungry, training costs are skyrocketing. Especially when lifelong learning is necessary, such as in recommender systems or…
NEWMA: a new method for scalable model-free online change-point detection
Nicolas Keriven, Damien Garreau, Iacopo Poli
We consider the problem of detecting abrupt changes in the distribution of a multi-dimensional time series, with limited computing power and memory. In this paper, we propose a new…