Stock, Pierre

12 publications

ICLR 2023 CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning Samuel Maddock, Alexandre Sablayrolles, Pierre Stock

ICMLW 2023 Green Federated Learning Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael Rabbat, Carole-Jean Wu, Ilya Mironov

ICML 2023 Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael Rabbat

ICML 2023 TAN Without a Burn: Scaling Laws of DP-SGD Tom Sander, Pierre Stock, Alexandre Sablayrolles

NeurIPSW 2022 Reconciling Security and Communication Efficiency in Federated Learning Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock

NeurIPSW 2022 The Interpolated MVU Mechanism for Communication-Efficient Private Federated Learning Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael Rabbat

ICCV 2021 LeViT: A Vision Transformer in ConvNet's Clothing for Faster Inference Benjamin Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze

CVPRW 2021 Low Bandwidth Video-Chat Compression Using Deep Generative Models Maxime Oquab, Pierre Stock, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie

ICLR 2021 Training with Quantization Noise for Extreme Model Compression Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Herve Jegou, Armand Joulin

ICLR 2020 And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou

ICLR 2019 Equi-Normalization of Neural Networks Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou

ECCV 2018 ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases Pierre Stock, Moustapha Cisse