| Entropy and mutual information in models of deep neural networks M Gabrié, A Manoel, C Luneau, J Barbier, N Macris, F Krzakala, ... Advances in Neural Information Processing Systems (NeurIPS), 1821-1831, 2018 | 184 | 2018 |
| 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 | 153 | 2022 |
| Swept approximate message passing for sparse estimation A Manoel, F Krzakala, E Tramel, L Zdeborova International Conference on Machine Learning (ICML), 1123-1132, 2015 | 89* | 2015 |
| Multi-layer generalized linear estimation A Manoel, F Krzakala, M Mézard, L Zdeborová 2017 IEEE International Symposium on Information Theory (ISIT), 2098-2102, 2017 | 65 | 2017 |
| Variational free energies for compressed sensing F Krzakala, A Manoel, EW Tramel, L Zdeborová 2014 IEEE International Symposium on Information Theory (ISIT), 1499-1503, 2014 | 61 | 2014 |
| 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 | 41 | 2022 |
| Deterministic and generalized framework for unsupervised learning with Restricted Boltzmann Machines EW Tramel, M Gabrié, A Manoel, F Caltagirone, F Krzakala Physical Review X 8 (4), 041006, 2018 | 39 | 2018 |
| 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 | 29* | 2022 |
| Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines EW Tramel, A Manoel, F Caltagirone, M Gabrié, F Krzakala 2016 IEEE Information Theory Workshop (ITW), 265-269, 2016 | 27 | 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 | 25 | 2020 |
| Approximate message-passing for convex optimization with non-separable penalties A Manoel, F Krzakala, G Varoquaux, B Thirion, L Zdeborová arXiv preprint arXiv:1809.06304, 2018 | 19 | 2018 |
| Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing A Manoel, F Krzakala, EW Tramel, L Zdeborová 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017 | 15 | 2017 |
| 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 | 10 | 2020 |
| 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 | 9 | 2022 |
| Expectation propagation J Raymond, A Manoel, M Opper Statistical Physics, Optimization, Inference, and Message-Passing Algorithms, 2015 | 9 | 2015 |
| TrojanPuzzle: Covertly Poisoning Code-Suggestion Models H Aghakhani, W Dai, A Manoel, X Fernandes, A Kharkar, C Kruegel, ... arXiv preprint arXiv:2301.02344, 2023 | 6 | 2023 |
| Statistical mechanics of reputation systems in autonomous networks A Manoel, R Vicente Journal of Statistical Mechanics: Theory and Experiment 2013 (08), P08002, 2013 | 3 | 2013 |
| 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, ... arXiv preprint arXiv:2309.11765, 2023 | 2 | 2023 |
| Project Florida: Federated Learning Made Easy DM Diaz, A Manoel, J Chen, N Singal, R Sim arXiv preprint arXiv:2307.11899, 2023 | 1 | 2023 |
| 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 | 1 | 2023 |
Florent KrzakalaÉcole polytechnique fédérale de LausanneVahvistettu sähköpostiosoite verkkotunnuksessa epfl.ch
