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2020 – today
- 2024
[c11]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. ICLR 2024- [i15]Mathieu Blondel, Vincent Roulet:
The Elements of Differentiable Programming. CoRR abs/2403.14606 (2024) - [i14]Vincent Roulet, Atish Agarwala, Jean-Bastien Grill, Grzegorz Swirszcz, Mathieu Blondel, Fabian Pedregosa:
Stepping on the Edge: Curvature Aware Learning Rate Tuners. CoRR abs/2407.06183 (2024) - 2023
- [j4]Corinne Jones
, Vincent Roulet, Zaïd Harchaoui:
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. J. Comput. Graph. Stat. 32(4): 1237-1247 (2023) - [j3]Vincent Roulet, Zaïd Harchaoui:
Target Propagation via Regularized Inversion for Recurrent Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. AISTATS 2023: 10112-10159 - [c9]Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
Modified Gauss-Newton Algorithms under Noise. SSP 2023: 51-55 - [i13]Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
Modified Gauss-Newton Algorithms under Noise. CoRR abs/2305.10634 (2023) - [i12]Vincent Roulet, Mathieu Blondel:
Dual Gauss-Newton Directions for Deep Learning. CoRR abs/2308.08886 (2023) - [i11]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. CoRR abs/2310.13863 (2023) - [i10]Vincent Roulet, Atish Agarwala, Fabian Pedregosa:
On the Interplay Between Stepsize Tuning and Progressive Sharpening. CoRR abs/2312.00209 (2023) - 2022
- [j2]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Discriminative clustering with representation learning with any ratio of labeled to unlabeled data. Stat. Comput. 32(1): 17 (2022) - [c8]Vincent Roulet, Zaïd Harchaoui:
Differentiable Programming A La Moreau. ICASSP 2022: 3498-3502 - [i9]Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui:
Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. CoRR abs/2207.06362 (2022) - [i8]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. CoRR abs/2212.05149 (2022) - 2021
- [c7]Vincent Roulet, Zaïd Harchaoui:
On the Smoothing of Deep Networks. CISS 2021: 1-6 - [i7]Vincent Roulet, Zaïd Harchaoui:
Target Propagation via Regularized Inversion. CoRR abs/2112.01453 (2021) - 2020
- [j1]Vincent Roulet, Alexandre d'Aspremont:
Sharpness, Restart, and Acceleration. SIAM J. Optim. 30(1): 262-289 (2020) - [c6]Vincent Roulet, Maryam Fazel, Siddhartha S. Srinivasa, Zaïd Harchaoui:
On the Convergence of the Iterative Linear Exponential Quadratic Gaussian Algorithm to Stationary Points. ACC 2020: 132-137 - [i6]Vincent Roulet, Zaïd Harchaoui:
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. CoRR abs/2002.09051 (2020) - [i5]Vincent Roulet, Zaïd Harchaoui:
Differentiable Programming à la Moreau. CoRR abs/2012.15458 (2020)
2010 – 2019
- 2019
- [c5]Vincent Roulet, Zaïd Harchaoui:
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. Allerton 2019: 84-91 - [c4]Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui:
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML 2019: 5518-5527 - [i4]Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
A Smoother Way to Train Structured Prediction Models. CoRR abs/1902.03228 (2019) - [i3]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Kernel-based Translations of Convolutional Networks. CoRR abs/1903.08131 (2019) - [i2]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
End-to-end Learning, with or without Labels. CoRR abs/1912.12979 (2019) - 2018
- [c3]Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
A Smoother Way to Train Structured Prediction Models. NeurIPS 2018: 4771-4783 - 2017
- [b1]Vincent Roulet:
Sur la géométrie de problèmes d'optimisation et leur structure. (On the geometry of optimization problems and their structure). École Normale Supérieure, Paris, France, 2017 - [c2]Damien Scieur, Vincent Roulet, Francis R. Bach, Alexandre d'Aspremont:
Integration Methods and Optimization Algorithms. NIPS 2017: 1109-1118 - [c1]Vincent Roulet, Alexandre d'Aspremont:
Sharpness, Restart and Acceleration. NIPS 2017: 1119-1129 - 2015
- [i1]Vincent Roulet, Fajwel Fogel, Alexandre d'Aspremont, Francis R. Bach:
Supervised Clustering in the Data Cube. CoRR abs/1506.04908 (2015)
Coauthor Index
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