11 citations · 22 across the 10 of their papers we have counts for
12 papers
Uniform error bounds for quantized dynamical models
Abdelkader Metakalard, Fabien Lauer, Kevin Colin +1
This paper provides statistical guarantees on the accuracy of dynamical models learned from dependent data sequences. Specifically, we develop uniform error bounds that apply to qu…
Uniform Risk Bounds for Learning with Dependent Data Sequences
Fabien Lauer
This paper extends standard results from learning theory with independent data to sequences of dependent data. Contrary to most of the literature, we do not rely on mixing argument…
Margin theory for the scenario-based approach to robust optimization in high dimension
Fabien Lauer
This paper deals with the scenario approach to robust optimization. This relies on a random sampling of the possibly infinite number of constraints induced by uncertainties in the…
Risk Bounds for Learning Multiple Components with Permutation-Invariant Losses
Fabien Lauer
This paper proposes a simple approach to derive efficient error bounds for learning multiple components with sparsity-inducing regularization. We show that for such regularization…
Rademacher Complexity and Generalization Performance of Multi-category Margin Classifiers
Khadija Musayeva, Fabien Lauer, Yann Guermeur
One of the main open problems in the theory of multi-category margin classification is the form of the optimal dependency of a guaranteed risk on the number C of categories, the sa…
On the exact minimization of saturated loss functions for robust regression and subspace estimation
Fabien Lauer
This paper deals with robust regression and subspace estimation and more precisely with the problem of minimizing a saturated loss function. In particular, we focus on computationa…
Error Bounds for Piecewise Smooth and Switching Regression
Fabien Lauer
The paper deals with regression problems, in which the nonsmooth target is assumed to switch between different operating modes. Specifically, piecewise smooth (PWS) regression cons…
Global optimization for low-dimensional switching linear regression and bounded-error estimation
Fabien Lauer
The paper provides global optimization algorithms for two particularly difficult nonconvex problems raised by hybrid system identification: switching linear regression and bounded-…
On the complexity of switching linear regression
Fabien Lauer
This technical note extends recent results on the computational complexity of globally minimizing the error of piecewise-affine models to the related problem of minimizing the erro…
On the complexity of piecewise affine system identification
Fabien Lauer
The paper provides results regarding the computational complexity of hybrid system identification. More precisely, we focus on the estimation of piecewise affine (PWA) maps from in…
Sparse phase retrieval via group-sparse optimization
Fabien Lauer, Henrik Ohlsson
This paper deals with sparse phase retrieval, i.e., the problem of estimating a vector from quadratic measurements under the assumption that few components are nonzero. In particul…
Finding sparse solutions of systems of polynomial equations via group-sparsity optimization
Fabien Lauer, Henrik Ohlsson
The paper deals with the problem of finding sparse solutions to systems of polynomial equations possibly perturbed by noise. In particular, we show how these solutions can be recov…