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2020 – today
- 2024
[c12]Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim:
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation. ICLR 2024- [c11]Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim:
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models. SP 2024: 1122-1140 - [i20]Tal Baumel, Andre Manoel, Daniel Jones, Shize Su, Huseyin A. Inan, Aaron Bornstein, Robert Sim:
Controllable Synthetic Clinical Note Generation with Privacy Guarantees. CoRR abs/2409.07809 (2024) - 2023
- [c10]Andre Manoel, Mirian del Carmen Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Robert Sim, Dan Miller, Danny Karmon, Dimitrios Dimitriadis:
Federated Multilingual Models for Medical Transcript Analysis. CHIL 2023: 147-162 - [c9]Prathamesh Mandke, Rachel Oberst, Matthias Reisser, Avijit Chakraborty, Christos Louizos, Joseph Soriaga, Daniel Madrigal Diaz, Andre Manoel, Nalin Singal, Jeff Omhover, Robert Sim:
Federated Learning Toolkit with Voice-based User Verification Demo. INTERSPEECH 2023: 5263-5264 - [i19]Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim:
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models. CoRR abs/2301.02344 (2023) - [i18]Daniel Madrigal Diaz, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim:
Project Florida: Federated Learning Made Easy. CoRR abs/2307.11899 (2023) - [i17]Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim:
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation. CoRR abs/2309.11765 (2023) - 2022
- [c8]Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang:
Differentially Private Fine-tuning of Language Models. ICLR 2022 - [c7]Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis:
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. IJCAI 2022: 2881-2887 - [i16]Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal Diaz, Andre Manoel, Robert Sim:
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations. CoRR abs/2203.13789 (2022) - [i15]Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis:
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. CoRR abs/2204.12703 (2022) - [i14]Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis:
Federated Multilingual Models for Medical Transcript Analysis. CoRR abs/2211.09722 (2022) - 2021
- [i13]Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang:
Differentially Private Fine-tuning of Language Models. CoRR abs/2110.06500 (2021) - 2020
- [i12]Mathieu Andreux
, Andre Manoel, Romuald Menuet, Charlie Saillard, Chloé Simpson:
Federated Survival Analysis with Discrete-Time Cox Models. CoRR abs/2006.08997 (2020)
2010 – 2019
- 2019
- [i11]Gaspar Rochette, Andre Manoel, Eric W. Tramel:
Efficient Per-Example Gradient Computations in Convolutional Neural Networks. CoRR abs/1912.06015 (2019) - 2018
- [c6]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. NeurIPS 2018: 1826-1836 - [i10]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. CoRR abs/1805.09785 (2018) - [i9]Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová:
Approximate message-passing for convex optimization with non-separable penalties. CoRR abs/1809.06304 (2018) - 2017
- [c5]Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová:
Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing. Allerton 2017: 1048-1055 - [c4]Andre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Multi-layer generalized linear estimation. ISIT 2017: 2098-2102 - [i8]Andre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Multi-Layer Generalized Linear Estimation. CoRR abs/1701.06981 (2017) - [i7]Eric W. Tramel, Marylou Gabrié, Andre Manoel, Francesco Caltagirone, Florent Krzakala:
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. CoRR abs/1702.03260 (2017) - [i6]Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová:
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing. CoRR abs/1706.00705 (2017) - 2016
- [c3]Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala:
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. ITW 2016: 265-269 - [i5]Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala:
Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines. CoRR abs/1606.03956 (2016) - [i4]Vinayak Abrol, Olivier Absil, Pierre-Antoine Absil, Sandrine Anthoine, Philippe Antoine, Thomas Arildsen, Nancy Bertin, Folkert Bleichrodt, Jérôme Bobin, Anne Bol, Antoine Bonnefoy, Francesco Caltagirone, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang:
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR abs/1609.04167 (2016) - 2015
- [c2]Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová:
Swept Approximate Message Passing for Sparse Estimation. ICML 2015: 1123-1132 - 2014
- [c1]Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborová:
Variational free energies for compressed sensing. ISIT 2014: 1499-1503 - [i3]Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborová:
Variational Free Energies for Compressed Sensing. CoRR abs/1402.1384 (2014) - [i2]Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová:
Sparse Estimation with the Swept Approximated Message-Passing Algorithm. CoRR abs/1406.4311 (2014) - 2012
- [i1]Andre Manoel, Renato Vicente:
Statistical mechanics of reputation systems in autonomous networks. CoRR abs/1211.6462 (2012)
Coauthor Index
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