Exploring Support Vector Machines for Higgs Parameter Analysis and L2 b-Tagger Efficiency

Jan 06, 2026

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This meeting focuses on the application of Support Vector Machines (SVMs) in analyzing Higgs parameters, evaluating efficiency and purity metrics. We will delve into feature space separability, kernel functions, and the calculation processes involved in SVMs. Additionally, we will discuss the performance of the L2 b-tagger, including its parameters, output, and correlation with QCD events, particularly concerning b and b-bar quarks. Join us for insights into optimizing machine learning methods for high-energy physics analysis.

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Exploring Support Vector Machines for Higgs Parameter Analysis and L2 b-Tagger Efficiency

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