Leonard Berrada

22 papers A* 2Journal 16Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Privacy Awareness for Information-Sharing Assistants: A Case-study on Form-filling with Contextual Integrity.
Trans. Mach. Learn. Res.
Sahra Ghalebikesabi, Eugene Bagdasarian, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle
2024 J jnl
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
CoRR
Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre
2024 J jnl
Operationalizing Contextual Integrity in Privacy-Conscious Assistants.
CoRR
Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle
2024 J jnl
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.
CoRR
Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz Gustavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas
2023 J jnl
ConvNets Match Vision Transformers at Scale.
CoRR
Samuel L. Smith, Andrew Brock, Leonard Berrada, Soham De
2023 J jnl
Differentially Private Diffusion Models Generate Useful Synthetic Images.
CoRR
Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle
2023 J jnl
Unlocking Accuracy and Fairness in Differentially Private Image Classification.
CoRR
Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle
2022 J jnl
A Stochastic Bundle Method for Interpolating Networks.
CoRR
Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel, M. Pawan Kumar
2022 J jnl
A Stochastic Bundle Method for Interpolation.
J. Mach. Learn. Res.
Alasdair Paren, Leonard Berrada, Rudra P. K. Poudel, M. Pawan Kumar
2022 J jnl
Unlocking High-Accuracy Differentially Private Image Classification through Scale.
CoRR
Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle
2021 J jnl
Comment on Stochastic Polyak Step-Size: Performance of ALI-G.
CoRR
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2021 A* conf
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications.
NeurIPS
Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar
2021 J jnl
Verifying Probabilistic Specifications with Functional Lagrangians.
CoRR
Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar
2020 A* conf
Training Neural Networks for and by Interpolation.
ICML
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2019 — conf
Deep Frank-Wolfe For Neural Network Optimization.
ICLR (Poster)
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2019 — —
Leveraging structure for optimization in deep learning.
Leonard Berrada
2019 J jnl
Training Neural Networks for and by Interpolation.
CoRR
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2018 J jnl
Deep Frank-Wolfe For Neural Network Optimization.
CoRR
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2018 — conf
Smooth Loss Functions for Deep Top-k Classification.
ICLR (Poster)
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2018 J jnl
Smooth Loss Functions for Deep Top-k Classification.
CoRR
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2017 — conf
Trusting SVM for Piecewise Linear CNNs.
ICLR (Poster)
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
2016 J jnl
Trusting SVM for Piecewise Linear CNNs.
CoRR
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar