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09/15/2023
An assessment of racial disparities in pretrial decision-making using misclassification models
Pretrial risk assessment tools are used in jurisdictions across the coun...
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08/17/2023
Sparse reconstruction of ordinary differential equations with inference
Sparse regression has emerged as a popular technique for learning dynami...
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03/17/2023
Statistical inference for association studies in the presence of binary outcome misclassification
In biomedical and public health association studies, binary outcome vari...
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07/29/2022
Kendall's Tau for Two-Sample Inference Problems
We consider a Kendall's tau measure between a binary group indicator and...
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06/30/2022
K-ARMA Models for Clustering Time Series Data
We present an approach to clustering time series data using a model-base...
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03/03/2022
Interpretable Latent Variables in Deep State Space Models
We introduce a new version of deep state-space models (DSSMs) that combi...
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01/18/2022
Fragility Measures For Typical Cases
The fragility index is a clinically motivated metric designed to supplem...
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12/31/2021
An empirical Bayes approach to estimating dynamic models of co-regulated gene expression
Time-course gene expression datasets provide insight into the dynamics o...
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07/05/2021
Clustering Structure of Microstructure Measures
This paper builds the clustering model of measures of market microstruct...
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06/27/2021
On Graphical Models and Convex Geometry
We introduce a mixture-model of beta distributions to identify significa...
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06/13/2021
A News-based Machine Learning Model for Adaptive Asset Pricing
The paper proposes a new asset pricing model – the News Embedding UMAP S...
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04/17/2021
Mixed Effect Modeling and Variable Selection for Quantile Regression
It is known that the estimating equations for quantile regression (QR) c...
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11/09/2020
Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model
The purpose of this paper is to test the multi-factor beta model implied...
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08/24/2020
Hierarchical Adaptive Lasso: Learning Sparse Neural Networks with Shrinkage via Single Stage Training
Deep neural networks achieve state-of-the-art performance in a variety o...
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05/25/2020
Robust Matrix Completion with Mixed Data Types
We consider the matrix completion problem of recovering a structured low...
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03/16/2020
Low-volatility Anomaly and the Adaptive Multi-Factor Model
The paper explains the low-volatility anomaly from a new perspective. We...
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10/25/2019
Quantile Regression Modelling via Location and Scale Mixtures of Normal Distributions
We show that the estimating equations for quantile regression can be sol...
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06/26/2019
Fairness criteria through the lens of directed acyclic graphical models
A substantial portion of the literature on fairness in algorithms propos...
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05/27/2019
Tuning Free Rank-Sparse Bayesian Matrix and Tensor Completion with Global-Local Priors
Matrix and tensor completion are frameworks for a wide range of problems...
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11/01/2018
Ludometrics: Luck, and How to Measure It
Game theory is the study of tractable games which may be used to model m...
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09/17/2018
Rank-based approach for estimating correlations in mixed ordinal data
High-dimensional mixed data as a combination of both continuous and ordi...
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04/23/2018
High Dimensional Estimation and Multi-Factor Models
The purpose of this paper is to re-investigate the estimation of multipl...
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03/26/2018
A Scalable Empirical Bayes Approach to Variable Selection in Generalized Linear Models
A new empirical Bayes approach to variable selection in the context of g...
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11/19/2017
A Double Parametric Bootstrap Test for Topic Models
Non-negative matrix factorization (NMF) is a technique for finding laten...
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10/22/2014
Penalized versus constrained generalized eigenvalue problems
We investigate the difference between using an ℓ_1 penalty versus an ℓ_1...
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03/24/2014
Simultaneous sparse estimation of canonical vectors in the p>>N setting
This article considers the problem of sparse estimation of canonical vec...
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01/21/2013
