Multi-input and Multi-variable systems
Constraints and Statical Determinacy
Per-Unit Sequence Models
Multicompartment Models: Overview
Routh-Hurwitz Criterion II
Routh-Hurwitz Criterion I
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Updated: Sep 3, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
QiangQiang Ren1, Chao Yuan1, Yifeng Zhao1
1College of Information and Electrical Engineering, China Agricultural University, 100083, Beijing, China.
This study introduces a novel multi-metric learning framework using pair constraints for efficient distance metric generalization. The proposed methods, including Multi-Birth Metric Learning (MBML), effectively handle complex data by jointly training global and local metrics.
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