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07/07/2023
Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization
This paper introduces a smooth method for (structured) sparsity in ℓ_q a...
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05/25/2022
Factorized Structured Regression for Large-Scale Varying Coefficient Models
Recommender Systems (RS) pervade many aspects of our everyday digital li...
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12/16/2021
Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches
Hearing loss is a major health problem and psychological burden in human...
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11/16/2021
Ocean Mover's Distance: Using Optimal Transport for Analyzing Oceanographic Data
Modern ocean datasets are large, multi-dimensional, and inherently spati...
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10/20/2021
GGLasso – a Python package for General Graphical Lasso computation
We introduce GGLasso, a Python package for solving General Graphical Las...
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08/20/2021
latentcor: An R Package for estimating latent correlations from mixed data types
We present `latentcor`, an R package for correlation estimation from dat...
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06/21/2021
A causal view on compositional data
Many scientific datasets are compositional in nature. Important examples...
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04/06/2021
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
This paper describes the implementation of semi-structured deep distribu...
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01/15/2021
STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations
Numerical methods for approximately solving partial differential equatio...
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12/11/2020
Learning physically consistent mathematical models from data using group sparsity
We propose a statistical learning framework based on group-sparse regres...
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11/02/2020
c-lasso – a Python package for constrained sparse and robust regression and classification
We introduce c-lasso, a Python package that enables sparse and robust li...
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06/24/2020
Fast computation of latent correlations
Latent Gaussian copula models provide a powerful means to perform multi-...
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07/17/2019
Stability selection enables robust learning of partial differential equations from limited noisy data
We present a statistical learning framework for robust identification of...
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03/04/2019
Regression models for compositional data: General log-contrast formulations, proximal optimization, and microbiome data applications
Compositional data sets are ubiquitous in science, including geology, ec...
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05/16/2018