| Sgd with large step sizes learns sparse features M Andriushchenko, AV Varre, L Pillaud-Vivien, N Flammarion International Conference on Machine Learning, 903-925, 2023 | 93 | 2023 |
| Why do we need weight decay in modern deep learning? F D'Angelo, M Andriushchenko, AV Varre, N Flammarion Advances in Neural Information Processing Systems 37, 23191-23223, 2024 | 71* | 2024 |
| Last iterate convergence of SGD for Least-Squares in the Interpolation regime. AV Varre, L Pillaud-Vivien, N Flammarion Advances in Neural Information Processing Systems 34, 21581-21591, 2021 | 59 | 2021 |
| On the spectral bias of two-layer linear networks AV Varre, ML Vladarean, L Pillaud-Vivien, N Flammarion Advances in neural information processing systems 36, 64380-64414, 2023 | 24 | 2023 |
| Accelerated sgd for non-strongly-convex least squares A Varre, N Flammarion Conference on Learning Theory, 2062-2126, 2022 | 13 | 2022 |
| Variants of homomorphism polynomials complete for algebraic complexity classes P Chaugule, N Limaye, A Varre ACM Transactions on Computation Theory (TOCT) 13 (4), 1-26, 2021 | 13 | 2021 |
| Learning In-context -grams with Transformers: Sub--grams Are Near-Stationary Points A Varre, G Yüce, N Flammarion Forty-second International Conference on Machine Learning, 2025 | 5 | 2025 |
| SGD vs GD: Rank Deficiency in Linear Networks AV Varre, M Sagitova, N Flammarion Advances in Neural Information Processing Systems 37, 60133-60161, 2024 | 1 | 2024 |
| Why Do We Need Weight Decay for Overparameterized Deep Networks? F D'Angelo, A Varre, M Andriushchenko, N Flammarion NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023 | 1 | 2023 |
| Incremental Learning in Transformers for In-Context Associative Recall A Varre, N Flammarion EurIPS 2025 Workshop on Principles of Generative Modeling (PriGM), 0 | | |
Nicolas FlammarionEPFLVerified email at epfl.ch
