14 citations · 37 across the 7 of their papers we have counts for
11 papers
Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches
Dominik Thalmeier, Gregor Miller, Elida Schneltzer +5
Hearing loss is a major health problem and psychological burden in humans. Mouse models offer a possibility to elucidate genes involved in the underlying developmental and pathophy…
Ocean Mover's Distance: Using Optimal Transport for Analyzing Oceanographic Data
Sangwon Hyun, Aditya Mishra, Christopher L. Follett +8
Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data st…
Instrumental Variable Estimation for Compositional Treatments
Elisabeth Ailer, Christian L. Müller, Niki Kilbertus
Many scientific datasets are compositional in nature. Important biological examples include species abundances in ecology, cell-type compositions derived from single-cell sequencin…
Robust Regression with Compositional Covariates
Aditya Mishra, Christian L. Muller
Many biological high-throughput data sets, such as targeted amplicon-based and metagenomic sequencing data, are compositional in nature. A common exploratory data analysis task is…
Regression models for compositional data: General log-contrast formulations, proximal optimization, and microbiome data applications
Patrick L. Combettes, Christian L. Müller
Compositional data sets are ubiquitous in science, including geology, ecology, and microbiology. In microbiome research, compositional data primarily arise from high-throughput seq…
Prediction Error Bounds for Linear Regression With the TREX
Jacob Bien, Irina Gaynanova, Johannes Lederer +1
The TREX is a recently introduced approach to sparse linear regression. In contrast to most well-known approaches to penalized regression, the TREX can be formulated without the us…
Perspective Functions: Proximal Calculus and Applications in High-Dimensional Statistics
Patrick L. Combettes, Christian L. Müller
Perspective functions arise explicitly or implicitly in various forms in applied mathematics and in statistical data analysis. To date, no systematic strategy is available to solve…
Non-convex Global Minimization and False Discovery Rate Control for the TREX
Jacob Bien, Irina Gaynanova, Johannes Lederer +1
The TREX is a recently introduced method for performing sparse high-dimensional regression. Despite its statistical promise as an alternative to the lasso, square-root lasso, and s…
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX
Johannes Lederer, Christian Müller
Lasso is a seminal contribution to high-dimensional statistics, but it hinges on a tuning parameter that is difficult to calibrate in practice. A partial remedy for this problem is…
Variable Metric Random Pursuit
Sebastian U. Stich, Christian L. Müller, Bernd Gärtner
We consider unconstrained randomized optimization of smooth convex objective functions in the gradient-free setting. We analyze Random Pursuit (RP) algorithms with fixed (F-RP) and…
Optimization of Convex Functions with Random Pursuit
Sebastian U. Stich, Christian L. Müller, Bernd Gärtner
We consider unconstrained randomized optimization of convex objective functions. We analyze the Random Pursuit algorithm, which iteratively computes an approximate solution to the…