6 citations · 9 across the 4 of their papers we have counts for
5 papers
From Prediction to Explainable Provider Behavior Profiles for Fraud, Waste, and Abuse Review
Yubin Park, Evan Brociner
Claims data can show that provider behavior changed but cannot by itself explain why. Fraud, waste, and abuse (FWA) review requires identifying material behavior, locating the code…
PaloBoost: An Overfitting-robust TreeBoost with Out-of-Bag Sample Regularization Techniques
Yubin Park, Joyce C. Ho
Stochastic Gradient TreeBoost is often found in many winning solutions in public data science challenges. Unfortunately, the best performance requires extensive parameter tuning an…
ACDC: -Carving Decision Chain for Risk Stratification
Yubin Park, Joyce Ho, Joydeep Ghosh
In many healthcare settings, intuitive decision rules for risk stratification can help effective hospital resource allocation. This paper introduces a novel variant of decision tre…
DPM: A State Space Model for Large-Scale Direct Marketing
Yubin Park, Rajiv Khanna, Joydeep Ghosh +1
We propose a novel statistical model to answer three challenges in direct marketing: which channel to use, which offer to make, and when to offer. There are several potential appli…
Perturbed Gibbs Samplers for Synthetic Data Release
Yubin Park, Joydeep Ghosh
We propose a categorical data synthesizer with a quantifiable disclosure risk. Our algorithm, named Perturbed Gibbs Sampler, can handle high-dimensional categorical data that are o…