Andre Manoel
Andre Manoel
Machine Learning Engineer,
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Citata da
Citata da
Differentially private fine-tuning of language models
D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ...
International Conference on Learning Representations (ICLR), 2022
Entropy and mutual information in models of deep neural networks
M Gabriť, A Manoel, C Luneau, J Barbier, N Macris, F Krzakala, ...
Advances in Neural Information Processing Systems (NeurIPS), 1821-1831, 2018
Swept approximate message passing for sparse estimation
A Manoel, F Krzakala, E Tramel, L Zdeborova
International Conference on Machine Learning (ICML), 1123-1132, 2015
Multi-layer generalized linear estimation
A Manoel, F Krzakala, M Mťzard, L ZdeborovŠ
2017 IEEE International Symposium on Information Theory (ISIT), 2098-2102, 2017
Heterogeneous ensemble knowledge transfer for training large models in federated learning
YJ Cho, A Manoel, G Joshi, R Sim, D Dimitriadis
Proceedings of the Thirty-First International Joint Conference on Artificial†…, 2022
Variational free energies for compressed sensing
F Krzakala, A Manoel, EW Tramel, L ZdeborovŠ
2014 IEEE International Symposium on Information Theory (ISIT), 1499-1503, 2014
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
MDCH Garcia, A Manoel, DD Madrigal, R Sim, D Dimitriadis
Workshop on Federated Learning: Recent Advances and New Challenges (in†…, 2022
Deterministic and generalized framework for unsupervised learning with Restricted Boltzmann Machines
EW Tramel, M Gabriť, A Manoel, F Caltagirone, F Krzakala
Physical Review X 8 (4), 041006, 2018
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines
EW Tramel, A Manoel, F Caltagirone, M Gabriť, F Krzakala
2016 IEEE Information Theory Workshop (ITW), 265-269, 2016
Federated Survival Analysis with Discrete-Time Cox Models
M Andreux, A Manoel, R Menuet, C Saillard, C Simpson
International Workshop on Federated Learning for User Privacy and Data†…, 2020
Approximate message-passing for convex optimization with non-separable penalties
A Manoel, F Krzakala, G Varoquaux, B Thirion, L ZdeborovŠ
arXiv preprint arXiv:1809.06304, 2018
Trojanpuzzle: Covertly poisoning code-suggestion models
H Aghakhani, W Dai, A Manoel, X Fernandes, A Kharkar, C Kruegel, ...
arXiv preprint arXiv:2301.02344, 2023
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing
A Manoel, F Krzakala, EW Tramel, L ZdeborovŠ
2017 55th Annual Allerton Conference on Communication, Control, and†…, 2017
Prediction of metabolic syndrome: A machine learning approach to help primary prevention
LD Tavares, A Manoel, THR Donato, F Cesena, CA Minanni, ...
Diabetes Research and Clinical Practice 191, 110047, 2022
Privacy-preserving in-context learning with differentially private few-shot generation
X Tang, R Shin, HA Inan, A Manoel, F Mireshghallah, Z Lin, S Gopi, ...
International Conference on Learning Representations (ICLR), 2023
Efficient Per-Example Gradient Computations in Convolutional Neural Networks
G Rochette, A Manoel, EW Tramel
Workshop on Theory and Practice of Differential Privacy (TPDP), 2020
Expectation propagation
J Raymond, A Manoel, M Opper
Statistical Physics, Optimization, Inference, and Message-Passing Algorithms, 2015
dp-transformers: Training transformer models with differential privacy
L Wutschitz, HA Inan, A Manoel
Federated Multilingual Models for Medical Transcript Analysis
A Manoel, MCH Garcia, T Baumel, S Su, J Chen, R Sim, D Miller, ...
Conference on Health, Inference, and Learning, 147-162, 2023
Project Florida: Federated learning made easy
DM Diaz, A Manoel, J Chen, N Singal, R Sim
arXiv preprint arXiv:2307.11899, 2023
Il sistema al momento non puÚ eseguire l'operazione. Riprova piý tardi.
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