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Collaborations and top research areas from the last five years
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On learning Gaussian multi-index models with gradient flow part I: General properties and two-timescale learning
Bietti, A., Bruna, J. & Pillaud-Vivien, L., 1 Dec 2025, In: Communications on Pure and Applied Mathematics. 78, 12, p. 2354-2435 82 p.Research output: Contribution to journal › Article › peer-review
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Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
Margossian, C. C., Pillaud-Vivien, L. & Saul, L. K., 1 Jan 2025, In: Journal of Machine Learning Research. 26, p. 1-41 41 p.Research output: Contribution to journal › Article › peer-review
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Batch and match: black-box variational inference with a score-based divergence
Cai, D., Modi, C., Pillaud-Vivien, L., Margossian, C. C., Gower, R. M., Blei, D. M. & Saul, L. K., 1 Jan 2024, In: Proceedings of Machine Learning Research. 235, p. 5258-5297 40 p.Research output: Contribution to journal › Conference article › peer-review
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Computational-Statistical Gaps in Gaussian Single-Index Models
Damian, A., Pillaud-Vivien, L., Lee, J. D. & Bruna, J., 1 Jan 2024, In: Proceedings of Machine Learning Research. 247, p. 1262 1 p.Research output: Contribution to journal › Conference article › peer-review
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Kernelized Diffusion Maps
Pillaud-Vivien, L. & Bach, F., 1 Jan 2023, In: Proceedings of Machine Learning Research. 195, p. 5236-5259 24 p.Research output: Contribution to journal › Conference article › peer-review
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On Single Index Models beyond Gaussian Data
Bruna, J., Pillaud-Vivien, L. & Zweig, A., 1 Jan 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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On the spectral bias of two-layer linear networks
Varre, A., Vladarean, M. L., Pillaud-Vivien, L. & Flammarion, N., 1 Jan 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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SGD with Large Step Sizes Learns Sparse Features
Andriushchenko, M., Varre, A., Pillaud-Vivien, L. & Flammarion, N., 1 Jan 2023, In: Proceedings of Machine Learning Research. 202, p. 903-925 23 p.Research output: Contribution to journal › Conference article › peer-review
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Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Boursier, E., Pillaud-Vivien, L. & Flammarion, N., 1 Jan 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation
Pillaud-Vivien, L., Reygner, J. & Flammarion, N., 1 Jan 2022, In: Proceedings of Machine Learning Research. 178, p. 2127-2159 33 p.Research output: Contribution to journal › Conference article › peer-review