Pretrial risk assessment tools are used in jurisdictions across the coun...
Sparse regression has emerged as a popular technique for learning dynami...
In biomedical and public health association studies, binary outcome vari...
We consider a Kendall's tau measure between a binary group indicator and...
We present an approach to clustering time series data using a model-base...
We introduce a new version of deep state-space models (DSSMs) that combi...
The fragility index is a clinically motivated metric designed to supplem...
Time-course gene expression datasets provide insight into the dynamics o...
This paper builds the clustering model of measures of market microstruct...
We introduce a mixture-model of beta distributions to identify significa...
The paper proposes a new asset pricing model – the News Embedding UMAP
S...
It is known that the estimating equations for quantile regression (QR) c...
The purpose of this paper is to test the multi-factor beta model implied...
Deep neural networks achieve state-of-the-art performance in a variety o...
We consider the matrix completion problem of recovering a structured low...
The paper explains the low-volatility anomaly from a new perspective. We...
We show that the estimating equations for quantile regression can be sol...
A substantial portion of the literature on fairness in algorithms propos...
Matrix and tensor completion are frameworks for a wide range of problems...
Game theory is the study of tractable games which may be used to model m...
High-dimensional mixed data as a combination of both continuous and ordi...
The purpose of this paper is to re-investigate the estimation of multipl...
A new empirical Bayes approach to variable selection in the context of
g...
Non-negative matrix factorization (NMF) is a technique for finding laten...
We investigate the difference between using an ℓ_1 penalty versus an
ℓ_1...
This article considers the problem of sparse estimation of canonical vec...
It is well known that in a supervised classification setting when the nu...