Smooth Loss Functions for Deep Top-k Classification L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2018 | 67 | 2018 |
Deep Frank-Wolfe For Neural Network Optimization L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2019 | 32 | 2019 |
Training neural networks for and by interpolation L Berrada, A Zisserman, MP Kumar International Conference on Machine Learning, 2020 | 24 | 2020 |
Trusting SVM for piecewise linear CNNs L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2017 | 16 | 2017 |
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications L Berrada, S Dathathri, K Dvijotham, R Stanforth, RR Bunel, J Uesato, ... Advances in Neural Information Processing Systems 34, 11136-11147, 2021 | 4* | 2021 |
Unlocking high-accuracy differentially private image classification through scale S De, L Berrada, J Hayes, SL Smith, B Balle arXiv preprint arXiv:2204.13650, 2022 | 3 | 2022 |
Comment on Stochastic Polyak Step-Size: Performance of ALI-G L Berrada, A Zisserman, MP Kumar arXiv preprint arXiv:2105.10011, 2021 | 1 | 2021 |
A Stochastic Bundle Method for Interpolating Networks A Paren, L Berrada, RPK Poudel, MP Kumar Journal of Machine Learning Research 23, 1-57, 2022 | | 2022 |
Leveraging structure for optimization in deep learning L Berrada University of Oxford, 2019 | | 2019 |