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Fatjon Zogaj
Fatjon Zogaj
ETH Zürich
在 ethz.ch 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Doing more with less: characterizing dataset downsampling for automl
F Zogaj, JP Cambronero, MC Rinard, J Cito
Proceedings of the VLDB Endowment 14 (11), 2059-2072, 2021
202021
N-1 experts: Unsupervised anomaly detection model selection
C Le Clei, Y Pushak, F Zogaj, MO Kareshk, Z Zohrevand, R Harlow, ...
First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022
42022
Expert-optimal correlation: contamination factor identification for unsupervised anomaly detection
Y Pushak, C Le Clei, F Zogaj, HF Moghadam, S Hong, H Chafi
US Patent App. 18/075,824, 2024
2024
Learning hyper-parameter scaling models for unsupervised anomaly detection
F Zogaj, Y Pushak, HF Moghadam, S Hong, H Chafi
US Patent App. 18/075,784, 2024
2024
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