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2020 – today
- 2024
[c10]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. ACL (Findings) 2024: 467-484- [i17]Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed:
Mixtral of Experts. CoRR abs/2401.04088 (2024) - 2023
- [j1]Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. IEEE Data Eng. Bull. 46(1): 67-78 (2023) - [c9]Samuel Maddock, Alexandre Sablayrolles, Pierre Stock:
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning. ICLR 2023 - [c8]Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael G. Rabbat:
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design. ICML 2023: 11888-11904 - [c7]Tom Sander, Pierre Stock, Alexandre Sablayrolles:
TAN Without a Burn: Scaling Laws of DP-SGD. ICML 2023: 29937-29949 - [i16]Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov:
Green Federated Learning. CoRR abs/2303.14604 (2023) - [i15]Xinchi Qiu, Ilias Leontiadis, Luca Melis, Alexandre Sablayrolles, Pierre Stock:
EXACT: Extensive Attack for Split Learning. CoRR abs/2305.12997 (2023) - [i14]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. CoRR abs/2305.17888 (2023) - [i13]Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed:
Mistral 7B. CoRR abs/2310.06825 (2023) - 2022
- [i12]Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles:
Defending against Reconstruction Attacks with Rényi Differential Privacy. CoRR abs/2202.07623 (2022) - [i11]Karthik Prasad, Sayan Ghosh, Graham Cormode
, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. CoRR abs/2207.12779 (2022) - [i10]Samuel Maddock, Alexandre Sablayrolles, Pierre Stock:
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning. CoRR abs/2210.02912 (2022) - [i9]Tom Sander, Pierre Stock, Alexandre Sablayrolles:
TAN without a burn: Scaling Laws of DP-SGD. CoRR abs/2210.03403 (2022) - [i8]Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Mike Rabbat:
The Interpolated MVU Mechanism For Communication-efficient Private Federated Learning. CoRR abs/2211.03942 (2022) - 2021
- [b1]Pierre Stock:
Efficiency and Redundancy in Deep Learning Models: Theoretical Considerations and Practical Applications. (Efficience et redondance dans les modèles d'apprentissage profond : considérations théoriques et applications pratiques). École normale supérieure de Lyon, France, 2021 - [c6]Maxime Oquab, Pierre Stock, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie:
Low Bandwidth Video-Chat Compression Using Deep Generative Models. CVPR Workshops 2021: 2388-2397 - [c5]Benjamin Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze:
LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference. ICCV 2021: 12239-12249 - [c4]Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin:
Training with Quantization Noise for Extreme Model Compression. ICLR 2021 - [i7]Benjamin Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze:
LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference. CoRR abs/2104.01136 (2021) - [i6]Pierre Stock, Rémi Gribonval:
An Embedding of ReLU Networks and an Analysis of their Identifiability. CoRR abs/2107.09370 (2021) - 2020
- [c3]Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou:
And the Bit Goes Down: Revisiting the Quantization of Neural Networks. ICLR 2020 - [i5]Angela Fan, Pierre Stock, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin:
Training with Quantization Noise for Extreme Model Compression. CoRR abs/2004.07320 (2020) - [i4]Maxime Oquab, Pierre Stock, Oran Gafni, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie:
Low Bandwidth Video-Chat Compression using Deep Generative Models. CoRR abs/2012.00328 (2020)
2010 – 2019
- 2019
- [c2]Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou:
Equi-normalization of Neural Networks. ICLR (Poster) 2019 - [i3]Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou:
Equi-normalization of Neural Networks. CoRR abs/1902.10416 (2019) - [i2]Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou:
And the Bit Goes Down: Revisiting the Quantization of Neural Networks. CoRR abs/1907.05686 (2019) - 2018
- [c1]Pierre Stock, Moustapha Cissé:
ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases. ECCV (6) 2018: 504-519 - 2017
- [i1]Pierre Stock, Moustapha Cissé:
ConvNets and ImageNet Beyond Accuracy: Explanations, Bias Detection, Adversarial Examples and Model Criticism. CoRR abs/1711.11443 (2017)
Coauthor Index
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