Andre Manoel

According to our database, Andre Manoel authored at least 22 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Differentially Private Fine-tuning of Language Models.

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

J. Priv. Confidentiality, 2024

Controllable Synthetic Clinical Note Generation with Privacy Guarantees.

Tal Baumel, Andre Manoel, Daniel Jones, Shize Su, Huseyin A. Inan, Aaron Bornstein, Robert Sim

CoRR, 2024

TrojanPuzzle: Covertly Poisoning Code-Suggestion Models.

Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim

Proceedings of the IEEE Symposium on Security and Privacy, 2024

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.

Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Project Florida: Federated Learning Made Easy.

Daniel Madrigal Diaz, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim

CoRR, 2023

Federated Learning Toolkit with Voice-based User Verification Demo.

Prathamesh Mandke, Rachel Oberst, Matthias Reisser, Avijit Chakraborty, Christos Louizos, Joseph Soriaga, Daniel Madrigal Diaz, Andre Manoel, Nalin Singal, Jeff Omhover, Robert Sim

Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Federated Multilingual Models for Medical Transcript Analysis.

Andre Manoel, Mirian del Carmen Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Robert Sim, Dan Miller, Danny Karmon, Dimitrios Dimitriadis

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations.

Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal Diaz, Andre Manoel, Robert Sim

CoRR, 2022

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning.

Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2020

Federated Survival Analysis with Discrete-Time Cox Models.

Mathieu Andreux, Andre Manoel, Romuald Menuet, Charlie Saillard, Chloé Simpson

CoRR, 2020

2019

Efficient Per-Example Gradient Computations in Convolutional Neural Networks.

Gaspar Rochette, Andre Manoel, Eric W. Tramel

CoRR, 2019

2018

Approximate message-passing for convex optimization with non-separable penalties.

Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová

CoRR, 2018

Entropy and mutual information in models of deep neural networks.

Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines.

Eric W. Tramel, Marylou Gabrié, Andre Manoel, Francesco Caltagirone, Florent Krzakala

CoRR, 2017

Multi-layer generalized linear estimation.

Andre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing.

Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16).

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

CoRR, 2016

Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines.

Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala

Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015

Swept Approximate Message Passing for Sparse Estimation.

Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Sparse Estimation with the Swept Approximated Message-Passing Algorithm.

Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová

CoRR, 2014

Variational free energies for compressed sensing.

Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborová

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2012

Statistical mechanics of reputation systems in autonomous networks

Andre Manoel, Renato Vicente

CoRR, 2012