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Iacopo Poli
Iacopo Poli
CTO, LightOn
Verified email at lighton.ai
Title
Cited by
Cited by
Year
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
J Launay, I Poli, F Boniface, F Krzakala
Advances in Neural Information Processing Systems 33, 2020
662020
RITA: a Study on Scaling Up Generative Protein Sequence Models
D Hesslow, N Zanichelli, P Notin, I Poli, D Marks
arXiv preprint arXiv:2205.05789, 2022
452022
NEWMA: a new method for scalable model-free online change-point detection
N Keriven, D Garreau, I Poli
IEEE Transactions on Signal Processing 68, 3515-3528, 2020
442020
Principled Training of Neural Networks with Direct Feedback Alignment
J Launay, I Poli, F Krzakala
arXiv preprint arXiv:1906.04554, 2019
322019
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
J Launay, I Poli, K Müller, G Pariente, I Carron, L Daudet, F Krzakala, ...
arXiv preprint arXiv:2012.06373, 2020
172020
Adversarial robustness by design through analog computing and synthetic gradients
A Cappelli, R Ohana, J Launay, L Meunier, I Poli, F Krzakala
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
102022
LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor
C Brossollet, A Cappelli, I Carron, C Chaintoutis, A Chatelain, L Daudet, ...
arXiv preprint arXiv:2107.11814, 2021
92021
Photonic Differential Privacy with Direct Feedback Alignment
R Ohana, H Medina, J Launay, A Cappelli, I Poli, L Ralaivola, ...
Advances in Neural Information Processing Systems 34, 2021
82021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients
A Cappelli, R Ohana, J Launay, L Meunier, I Poli
ICML 2021 Workshop on Adversarial Machine Learning, 2021
62021
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks
J Launay, I Poli, K Müller, I Carron, L Daudet, F Krzakala, S Gigan
arXiv preprint arXiv:2006.01475, 2020
62020
PAGnol: An Extra-Large French Generative Model
J Launay, EL Tommasone, B Pannier, F Boniface, A Chatelain, A Cappelli, ...
arXiv preprint arXiv:2110.08554, 2021
52021
Contrastive Embeddings for Neural Architectures
D Hesslow, I Poli
arXiv preprint arXiv:2102.04208, 2021
52021
Is the Number of Trainable Parameters All That Actually Matters?
A Chatelain, A Djeghri, D Hesslow, J Launay
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 27-32, 2022
42022
Method and system for machine learning using optical data
I Poli, J Launay, K Müller, G Pariente, I Carron, L Daudet
US Patent 11,137,289, 2021
42021
Method and system for distributed training using synthetic gradients
J Launay, I Poli, K Müller, G Pariente, I Carron, L Daudet
US Patent App. 17/117,925, 2022
22022
METHOD AND SYSTEM FOR MACHINE LEARNING USING OPTICAL DATA
I Poli, J Launay, K Müller, G Pariente, I Carron, L Daudet, R Ohana, ...
US Patent App. 17/331,240, 2021
22021
Binarization for Optical Processing Units via REINFORCE
B Kozyrskiy, I Poli, R Ohana, L Daudet, I Carron, M Filippone
Proceedings of the 3rd International Conference on Advances in Signal …, 2021
12021
Online Change Point Detection in Molecular Dynamics With Optical Random Features
A Chatelain, E Tommasone, L Daudet, I Poli
arXiv preprint arXiv:2006.08697, 2020
12020
Learning Binary Data Representation for Optical Processing Units
B Kozyrskiy, M Filippone, I Poli, R Ohana, L Daudet, I Carron
Sensors & Transducers 256 (2), 1-11, 2022
2022
Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra
D Hesslow, A Cappelli, I Carron, L Daudet, R Lafargue, K Müller, ...
arXiv preprint arXiv:2104.14429, 2021
2021
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