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Computational approaches to non-convex, sparsity-inducing multi-penalty regularization." Inverse Problems (2021)."
Estimating covariance and precision matrices along subspaces." Electronic Journal of Statistics (2021)."
Automated parameter estimation for selected inverse problems In Grenoble, France., 2019.
Covariance and precision matrix estimation, and dimension reduction in regression problems In Oslo, Norway., 2019.
Linear convergence and support recovery for non-convex multi-penalty regularization. SPARS 2019, Toulouse, France, 2019.
Monte Carlo wavelets: a randomized approach to frame discretization In Sampling Theory and Applications. IEEE, 2019.
Nonlinear generalization of the monotone single index model." Information and Inference (2019)."
Towards nonlinear sufficient dimension reduction In AIP conference, Grenoble, France., 2019.
Unsupervised parameter selection for denoising with the elastic net." Machine Learning (2019)."
Unsupervised Parameter Selection in Variational Regularization. SPARS 2019, Toulouse, France, 2019.
Analysis of edge and corner points using parabolic dictionaries." Applied and Computational Harmonic Analysis (2018)."
A geometrical approach for nonlinear single-index model estimation. ICML Workshop Stockholm, 2018.
High-dimensional function learning on curves. Cambridge, UK, 2018.
Inference and estimation for nonlinear single index models. Machine Learning Summer School Spain, 2018.
A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net." arXiv (2018)."
A machine learning approach for adaptive parameter selection In University of Oslo, Norway., 2018.
A machine learning approach to optimal regularization In European Women in Mathematics, Graz, Austria., 2018.
A machine learning approach to optimal regularization: Affine Manifolds In NTNU, Norway., 2018.
Nonlinear estimation of single index models In Nonlinear Data: Theory and Algorithms Oberwolfach., 2018.
Nearly Optimal Parameter selection for the Elastic Net In Hangzhou, China., 2017.