research
∙
08/02/2023
Improved convergence rates of nonparametric penalized regression under misspecified total variation
Penalties that induce smoothness are common in nonparametric regression....
share
research
∙
11/06/2022
A framework for leveraging machine learning tools to estimate personalized survival curves
The conditional survival function of a time-to-event outcome subject to ...
research
∙
06/24/2022
Accounting for Inconsistent Use of Covariate Adjustment in Group Sequential Trials
Group sequential designs are common in clinical trials, as they allow fo...
research
∙
06/07/2022
Regression in Tensor Product Spaces by the Method of Sieves
Estimation of a conditional mean (linking a set of features to an outcom...
research
∙
12/07/2021
Mesh-Based Solutions for Nonparametric Penalized Regression
It is often of interest to estimate regression functions non-parametrica...
research
∙
07/13/2021
The Future will be Different than Today: Model Evaluation Considerations when Developing Translational Clinical Biomarker
Finding translational biomarkers stands center stage of the future of pe...
research
∙
05/05/2021
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure
Originally developed for imputing missing entries in low rank, or approx...
research
∙
04/02/2021
A Sieve Stochastic Gradient Descent Estimator for Online Nonparametric Regression in Sobolev ellipsoids
The goal of regression is to recover an unknown underlying function that...
research
∙
04/01/2021
An Online Projection Estimator for Nonparametric Regression in Reproducing Kernel Hilbert Spaces
The goal of nonparametric regression is to recover an underlying regress...
research
∙
05/11/2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets
Neural networks have seen limited use in prediction for high-dimensional...
research
∙
04/11/2020
Spatial Matrix Completion for Spatially-Misaligned and High-Dimensional Air Pollution Data
In health-pollution cohort studies, accurate predictions of pollutant co...
research
∙
03/01/2020
A flexible Bayesian framework to estimate age- and cause-specific child mortality over time from sample registration data
In order to implement disease-specific interventions in young age groups...
research
∙
02/28/2020
BigSurvSGD: Big Survival Data Analysis via Stochastic Gradient Descent
In many biomedical applications, outcome is measured as a “time-to-event...
research
∙
12/28/2019
Approval policies for modifications to Machine Learning-Based Software as a Medical Device: A study of bio-creep
Successful deployment of machine learning algorithms in healthcare requi...
research
∙
06/13/2019
Selective prediction-set models with coverage guarantees
Though black-box predictors are state-of-the-art for many complex tasks,...
research
∙
05/29/2019
Using Propensity Scores to Develop and Evaluate Treatment Rules with Observational Data
In this paper, we outline a principled approach to estimate an individua...
research
∙
03/29/2019
Estimation of cell lineage trees by maximum-likelihood phylogenetics
CRISPR technology has enabled large-scale cell lineage tracing for compl...
research
∙
03/28/2019
An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression
In the regression setting, given a set of hyper-parameters, a model-esti...
research
∙
03/11/2019
Generalized Sparse Additive Models
We present a unified framework for estimation and analysis of generalize...
research
∙
03/11/2019
Wavelet regression and additive models for irregularly spaced data
We present a novel approach for nonparametric regression using wavelet b...
research
∙
11/21/2017
Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification
Neural networks are usually not the tool of choice for nonparametric hig...
research
∙
11/11/2017
Survival analysis of DNA mutation motifs with penalized proportional hazards
Antibodies, an essential part of our immune system, develop in an intric...
research
∙
03/28/2017
Gradient-based Regularization Parameter Selection for Problems with Non-smooth Penalty Functions
In high-dimensional and/or non-parametric regression problems, regulariz...
research
∙
10/13/2014
Convex Modeling of Interactions with Strong Heredity
We consider the task of fitting a regression model involving interaction...
research
∙
09/18/2014
Fused Lasso Additive Model
We consider the problem of predicting an outcome variable using p covari...
research
∙
05/16/2014
Selection Bias Correction and Effect Size Estimation under Dependence
We consider large-scale studies in which it is of interest to test a ver...
research
∙
11/26/2013
A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression
In this paper we purpose a blockwise descent algorithm for group-penaliz...
research
∙
11/15/2013
On Estimating Many Means, Selection Bias, and the Bootstrap
With recent advances in high throughput technology, researchers often fi...
research
∙
06/27/2012
A Permutation Approach to Testing Interactions in Many Dimensions
To date, testing interactions in high dimensions has been a challenging ...
research
∙
11/07/2011
Discriminant Analysis with Adaptively Pooled Covariance
Linear and Quadratic Discriminant analysis (LDA/QDA) are common tools fo...
research
∙
11/09/2010
