Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning

Research output: Working paper/Preprint › Preprint

Keywords

@techreport{e10a1943160c4fcd8a5611e7a063189b,

title = "Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning",

keywords = "selection bias, metric learning, semi-supervised learning, diversity",

author = "Y.I. Tepeli and {de Wolf}, M.J. and {P. Gon{\c c}alves}, Joana",

year = "2024",

month = nov,

day = "27",

doi = "10.48550/arXiv.2411.18442",

language = "English",

type = "WorkingPaper",

}

TY - UNPB

T1 - Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning

AU - Tepeli, Y.I.

AU - de Wolf, M.J.

AU - P. Gonçalves, Joana

PY - 2024/11/27

Y1 - 2024/11/27

KW - selection bias

KW - metric learning

KW - semi-supervised learning

KW - diversity

U2 - 10.48550/arXiv.2411.18442

DO - 10.48550/arXiv.2411.18442

M3 - Preprint

BT - Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning

ER -