research
∙
05/24/2023
Generative AI for Bayesian Computation
Generative AI (Gen-AI) methods are developed for Bayesian Computation. G...
share
research
∙
05/04/2023
Quantile Importance Sampling
In Bayesian inference, the approximation of integrals of the form ψ = 𝔼_...
research
∙
06/20/2022
Deep Partial Least Squares for Empirical Asset Pricing
We use deep partial least squares (DPLS) to estimate an asset pricing mo...
research
∙
05/29/2019
Bayesian Inference for Polya Inverse Gamma Models
Probability density functions that include the gamma function are widely...
research
∙
04/24/2019
Horseshoe Regularization for Machine Learning in Complex and Deep Models
Since the advent of the horseshoe priors for regularization, global-loca...
research
∙
03/22/2019
Scalable Data Augmentation for Deep Learning
Scalable Data Augmentation (SDA) provides a framework for training deep ...
research
∙
03/18/2019
Deep Fundamental Factor Models
Deep fundamental factor models are developed to interpret and capture no...
research
∙
02/17/2019
Bayesian Regularization: From Tikhonov to Horseshoe
Bayesian regularization is a central tool in modern-day statistical and ...
research
∙
08/26/2018
Bayesian Hypothesis Testing: Redux
Bayesian hypothesis testing is re-examined from the perspective of an a ...
research
∙
07/20/2018
Deep Learning
Deep learning (DL) is a high dimensional data reduction technique for co...
research
∙
05/03/2018
Deep Factor Alpha
Deep Factor Alpha provides a framework for extracting nonlinear factors ...
research
∙
04/25/2018
Deep Learning for Predicting Asset Returns
Deep learning searches for nonlinear factors for predicting asset return...
research
∙
03/12/2018
Weighted Bayesian Bootstrap for Scalable Bayes
We develop a weighted Bayesian Bootstrap (WBB) for machine learning and ...
research
∙
05/31/2017
Bayesian l_0 Regularized Least Squares
Bayesian l_0-regularized least squares provides a variable selection tec...
research
∙
05/27/2017
Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading
Deep learning applies hierarchical layers of hidden variables to constru...
research
∙
02/23/2017
Horseshoe Regularization for Feature Subset Selection
Feature subset selection arises in many high-dimensional applications of...
research
∙
09/20/2015
A Statistical Theory of Deep Learning via Proximal Splitting
In this paper we develop a statistical theory and an implementation of d...
research
∙
02/11/2015
Proximal Algorithms in Statistics and Machine Learning
In this paper we develop proximal methods for statistical learning. Prox...
research
∙
05/02/2012
Bayesian inference for logistic models using Polya-Gamma latent variables
We propose a new data-augmentation strategy for fully Bayesian inference...
research
∙
09/11/2011