47 citations · 103 across the 13 of their papers we have counts for
Showing 2018Show all
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physics.data-an2018★ 2 cited
Understanding the boosted decision tree methods with the weak-learner approximation
Li-Gang Xia
Two popular boosted decsion tree (BDT) methods, Adaptive BDT (AdaBDT) and Gradient BDT (GradBDT) are studied in the classification problem of separating signal from background assu…
physics.data-an2018★ 28 cited
QBDT, a new boosting decision tree method with systematic uncertainties into training for High Energy Physics
Li-Gang Xia
A new boosting decision tree (BDT) method, QBDT, is proposed for the classification problem in the field of high energy physics (HEP). In many HEP researches, great efforts are mad…
physics.data-an2018★ 5 cited
Study of constraint and impact of a nuisance parameter in maximum likelihood method
Li-Gang Xia
Maximum likelihood method is widely used for parameter estimation in high energy physics. To consider various systematic uncertainties, tens of or even hundreds of nuisance paramet…