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Overall Objectives
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography


Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

International Conferences with Proceedings

  • 9A. Bietti, G. Mialon, D. Chen, J. Mairal.

    A Kernel Perspective for Regularizing Deep Neural Networks, in: ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, Proceedings of Machine Learning Research, June 2019, vol. 97, pp. 664-674, https://arxiv.org/abs/1810.00363.

    https://hal.inria.fr/hal-01884632
  • 10R. Bollapragada, D. Scieur, A. D'Aspremont.

    Nonlinear Acceleration of Momentum and Primal-Dual Algorithms, in: AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics, Naha, Japan, The 22nd International Conference on Artificial Intelligence and Statistics,, April 2019, vol. 89, https://arxiv.org/abs/1810.04539. [ DOI : 10.04539 ]

    https://hal.archives-ouvertes.fr/hal-01893921
  • 11T. Kerdreux, A. D'Aspremont, S. Pokutta.

    Restarting Frank-Wolfe, in: AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics, Naha, Japan, Proceedings of Machine Learning Research, April 2019, vol. 89, https://arxiv.org/abs/1810.02429. [ DOI : 10.02429 ]

    https://hal.archives-ouvertes.fr/hal-01893922
  • 12U. Marteau-Ferey, F. Bach, A. Rudi.

    Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses, in: NeurIPS 2019 - Conference on Neural Information Processing Systems, Vancouver, Canada, December 2019, https://arxiv.org/abs/1907.01771.

    https://hal.inria.fr/hal-02169626
  • 13T. Ryffel, E. Dufour-Sans, R. Gay, F. Bach, D. Pointcheval.

    Partially Encrypted Machine Learning using Functional Encryption, in: NeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, Advances in Neural Information Processing Systems, December 2019, https://arxiv.org/abs/1905.10214.

    https://hal.inria.fr/hal-02357181
  • 14A. Taylor, F. Bach.

    Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions, in: COLT 2019 - Conference on Learning Theory, Phoenix, United States, June 2019, https://arxiv.org/abs/1902.00947 - 12 pages + appendix; code available at https://github.com/AdrienTaylor/Potential-functions-for-first-order-methods.

    https://hal.inria.fr/hal-02009309

Conferences without Proceedings

Other Publications