| Publication | Date of Publication | Type |
|---|
| An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization | 2023-05-25 | Paper |
| Regularization properties of dual subgradient flow | 2023-05-11 | Paper |
| Zeroth-order optimization with orthogonal random directions | 2023-05-02 | Paper |
| Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry | 2023-03-01 | Paper |
| Implicit regularization with strongly convex bias: Stability and acceleration | 2023-02-10 | Paper |
| For interpolating kernel machines, minimizing the norm of the ERM solution maximizes stability | 2023-02-10 | Paper |
| From inexact optimization to learning via gradient concentration | 2023-01-16 | Paper |
| Understanding neural networks with reproducing kernel Banach spaces | 2022-12-08 | Paper |
| An elementary analysis of ridge regression with random design | 2022-10-12 | Paper |
| Constructing Fast Approximate Eigenspaces With Application to the Fast Graph Fourier Transforms | 2022-09-23 | Paper |
| Fast iterative regularization by reusing data | 2022-04-21 | Paper |
| An elementary analysis of ridge regression with random design | 2022-03-16 | Paper |
| Regularization: From Inverse Problems to Large-Scale Machine Learning | 2022-02-08 | Paper |
| Iterative regularization for low complexity regularizers | 2022-02-01 | Paper |
| Multi-scale vector quantization with reconstruction trees | 2021-12-16 | Paper |
| Understanding neural networks with reproducing kernel Banach spaces | 2021-09-20 | Paper |
| Reproducing kernel Hilbert spaces on manifolds: Sobolev and diffusion spaces | 2021-06-23 | Paper |
| From inexact optimization to learning via gradient concentration | 2021-06-09 | Paper |
| Construction and Monte Carlo estimation of wavelet frames generated by a reproducing kernel | 2021-05-06 | Paper |
| Convergence of stochastic proximal gradient algorithm | 2021-04-22 | Paper |
| Accelerated Iterative Regularization via Dual Diagonal Descent | 2021-03-10 | Paper |
| Faster Kriging: Facing High-Dimensional Simulators | 2020-11-04 | Paper |
| https://portal.mardi4nfdi.de/entity/Q4969161 | 2020-10-05 | Paper |
| Neurally plausible mechanisms for learning selective and invariant representations | 2020-10-01 | Paper |
| Thresholding gradient methods in Hilbert spaces: support identification and linear convergence | 2020-05-11 | Paper |
| Optimal rates for spectral algorithms with least-squares regression over Hilbert spaces | 2020-02-28 | Paper |
| Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms | 2020-02-22 | Paper |
| A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings | 2020-02-13 | Paper |
| Fast approximation of orthogonal matrices and application to PCA | 2019-07-18 | Paper |
| Monte Carlo wavelets: a randomized approach to frame discretization | 2019-03-15 | Paper |
| Modified Fejér sequences and applications | 2018-10-02 | Paper |
| Generalization properties of doubly stochastic learning algorithms | 2018-06-01 | Paper |
| Optimal Rates for Multi-pass Stochastic Gradient Methods | 2018-04-17 | Paper |
| Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability | 2018-03-02 | Paper |
| Iterative regularization via dual diagonal descent | 2018-03-01 | Paper |
| On invariance and selectivity in representation learning | 2018-02-19 | Paper |
| A First-Order Stochastic Primal-Dual Algorithm with Correction Step | 2017-09-13 | Paper |
| Multiscale geometric methods for data sets. I: Multiscale SVD, noise and curvature. | 2017-09-07 | Paper |
| Generalization Properties of Doubly Stochastic Learning Algorithms | 2017-07-03 | Paper |
| Convergence of the Forward-Backward Algorithm: Beyond the Worst Case with the Help of Geometry | 2017-03-28 | Paper |
| Iterative Regularization for Learning with Convex Loss Functions | 2016-06-06 | Paper |
| Unsupervised learning of invariant representations | 2016-06-01 | Paper |
| A stochastic inertial forward–backward splitting algorithm for multivariate monotone inclusions | 2016-05-31 | Paper |
| Stochastic forward-backward splitting for monotone inclusions | 2016-05-27 | Paper |
| On Learnability, Complexity and Stability | 2015-07-20 | Paper |
| A stochastic inertial forward-backward splitting algorithm for multivariate monotone inclusions | 2015-07-03 | Paper |
| Stochastic inertial primal-dual algorithms | 2015-07-03 | Paper |
| Nonparametric sparsity and regularization | 2014-12-08 | Paper |
| https://portal.mardi4nfdi.de/entity/Q2933941 | 2014-12-08 | Paper |
| Proximal methods for the latent group lasso penalty | 2014-09-26 | Paper |
| Learning sets with separating kernels | 2014-07-18 | Paper |
| A Stochastic forward-backward splitting method for solving monotone inclusions in Hilbert spaces | 2014-03-31 | Paper |
| Some Recent Advances in Multiscale Geometric Analysis of Point Clouds | 2012-09-26 | Paper |
| Kernels for Vector-Valued Functions: A Review | 2012-08-08 | Paper |
| Multi-output learning via spectral filtering | 2012-07-31 | Paper |
| https://portal.mardi4nfdi.de/entity/Q2896059 | 2012-07-13 | Paper |
| Consistency of learning algorithms using Attouch–Wets convergence | 2012-03-15 | Paper |
| https://portal.mardi4nfdi.de/entity/Q3093228 | 2011-10-12 | Paper |
| https://portal.mardi4nfdi.de/entity/Q3093282 | 2011-10-12 | Paper |
| Adaptive kernel methods using the balancing principle | 2010-10-06 | Paper |
| Mathematics of the neural response | 2010-03-12 | Paper |
| Elastic-net regularization in learning theory | 2009-06-11 | Paper |
| Spectral Algorithms for Supervised Learning | 2008-07-03 | Paper |
| On early stopping in gradient descent learning | 2007-09-06 | Paper |
| On regularization algorithms in learning theory | 2007-03-12 | Paper |
| DISCRETIZATION ERROR ANALYSIS FOR TIKHONOV REGULARIZATION | 2006-04-06 | Paper |
| Model selection for regularized least-squares algorithm in learning theory | 2006-01-23 | Paper |
| Are Loss Functions All the Same? | 2005-01-04 | Paper |
