‪Nurbek Tastan‬ - ‪Google Scholar‬

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Citata da

	Tutte	Dal 2019
Citazioni	9	9
Indice H	2	2
i10-index	0	0

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4

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Coautori

Karthik NandakumarMohamed Bin Zayed University of Artificial Intelligence (MBZUAI)Email verificata su mbzuai.ac.ae
Anas Al-lahhamMohamed Bin Zayed University of Artificial Intelligence (MBZUAI)Email verificata su mbzuai.ac.ae
Zaigham ZaheerMohamed bin Zayed University of Artificial IntelligenceEmail verificata su mbzuai.ac.ae

Nurbek Tastan

Nurbek Tastan

MBZUAI

Email verificata su mbzuai.ac.ae

Trustworthy AI Federated Learning Machine Learning Computer Vision


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Valid and Invalid Bitcoin Transactions S Amanzholova, N Tastan, K Kalkamanova, A Yessenalina Proceedings of the 6th International Conference on Engineering & MIS 2020, 1-5, 2020	5	2020
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection A Al-lahham, N Tastan, MZ Zaheer, K Nandakumar Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024	2	2024
CaPriDe Learning: Confidential and Private Decentralized Learning Based on Encryption-Friendly Distillation Loss N Tastan, K Nandakumar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	2	2023
Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline A Al-lahham, MZ Zaheer, N Tastan, K Nandakumar arXiv preprint arXiv:2404.00847, 2024		2024
Confidential and Private Decentralized Learning based on Encryption-friendly Distillation Loss N Tastan		2023

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