Search Results for author: Alexandre Sablayrolles

Found 16 papers, 10 papers with code

Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms

no code implementations12 Apr 2022 Saeed Mahloujifar, Alexandre Sablayrolles, Graham Cormode, Somesh Jha

A common countermeasure against MI attacks is to utilize differential privacy (DP) during model training to mask the presence of individual examples.

Defending against Reconstruction Attacks with Rényi Differential Privacy

no code implementations15 Feb 2022 Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles

Reconstruction attacks allow an adversary to regenerate data samples of the training set using access to only a trained model.

Watermarking Images in Self-Supervised Latent Spaces

1 code implementation17 Dec 2021 Pierre Fernandez, Alexandre Sablayrolles, Teddy Furon, Hervé Jégou, Matthijs Douze

We revisit watermarking techniques based on pre-trained deep networks, in the light of self-supervised approaches.

Data Augmentation

Nearest neighbor search with compact codes: A decoder perspective

no code implementations17 Dec 2021 Kenza Amara, Matthijs Douze, Alexandre Sablayrolles, Hervé Jégou

Modern approaches for fast retrieval of similar vectors on billion-scaled datasets rely on compressed-domain approaches such as binary sketches or product quantization.

Quantization

Opacus: User-Friendly Differential Privacy Library in PyTorch

1 code implementation25 Sep 2021 Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov

We introduce Opacus, a free, open-source PyTorch library for training deep learning models with differential privacy (hosted at opacus. ai).

Going deeper with Image Transformers

14 code implementations ICCV 2021 Hugo Touvron, Matthieu Cord, Alexandre Sablayrolles, Gabriel Synnaeve, Hervé Jégou

In particular, we investigate the interplay of architecture and optimization of such dedicated transformers.

Ranked #3 on Image Classification on CIFAR-10 (using extra training data)

Image Classification Transfer Learning

White-box vs Black-box: Bayes Optimal Strategies for Membership Inference

no code implementations29 Aug 2019 Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier, Cordelia Schmid, Hervé Jégou

Membership inference determines, given a sample and trained parameters of a machine learning model, whether the sample was part of the training set.

Large Memory Layers with Product Keys

7 code implementations NeurIPS 2019 Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou

In our experiments we consider a dataset with up to 30 billion words, and we plug our memory layer in a state-of-the-art transformer-based architecture.

Language Modelling

Déjà Vu: an empirical evaluation of the memorization properties of ConvNets

no code implementations ICLR 2019 Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Hervé Jégou

Convolutional neural networks memorize part of their training data, which is why strategies such as data augmentation and drop-out are employed to mitigate overfitting.

Data Augmentation

Spreading vectors for similarity search

1 code implementation ICLR 2019 Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Hervé Jégou

Discretizing multi-dimensional data distributions is a fundamental step of modern indexing methods.

Quantization

Link and code: Fast indexing with graphs and compact regression codes

5 code implementations CVPR 2018 Matthijs Douze, Alexandre Sablayrolles, Hervé Jégou

Similarity search approaches based on graph walks have recently attained outstanding speed-accuracy trade-offs, taking aside the memory requirements.

Image Similarity Search Quantization

How should we evaluate supervised hashing?

1 code implementation21 Sep 2016 Alexandre Sablayrolles, Matthijs Douze, Hervé Jégou, Nicolas Usunier

Hashing produces compact representations for documents, to perform tasks like classification or retrieval based on these short codes.

General Classification Transfer Learning

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