Follow
Amirmasoud Ghiassi
Amirmasoud Ghiassi
PhD candidate, TU Delft
Verified email at tudelft.nl
Title
Cited by
Cited by
Year
Masa: Responsive multi-dnn inference on the edge
B Cox, J Galjaard, A Ghiassi, R Birke, LY Chen
2021 IEEE International Conference on Pervasive Computing and Communications …, 2021
282021
Robust (deep) learning framework against dirty labels and beyond
A Ghiassi, T Younesian, Z Zhao, R Birke, V Schiavoni, LY Chen
2019 First IEEE International Conference on Trust, Privacy and Security in …, 2019
142019
Qactor: Active learning on noisy labels
T Younesian, Z Zhao, A Ghiassi, R Birke, LY Chen
Asian Conference on Machine Learning, 548-563, 2021
132021
Online label aggregation: A variational bayesian approach
C Hong, A Ghiassi, Y Zhou, R Birke, LY Chen
Proceedings of the Web Conference 2021, 1904-1915, 2021
8*2021
Mema: Fast inference of multiple deep models
J Galjaard, B Cox, A Ghiassi, LY Chen, R Birke
2021 IEEE International Conference on Pervasive Computing and Communications …, 2021
72021
Trusted loss correction for noisy multi-label learning
A Ghiassi, CO Pene, R Birke, LY Chen
Asian Conference on Machine Learning, 343-358, 2023
52023
Qactor: On-line active learning for noisy labeled stream data
T Younesian, Z Zhao, A Ghiassi, R Birke, LY Chen
arXiv preprint arXiv:2001.10399, 2020
52020
Trustnet: Learning from trusted data against (a) symmetric label noise
A Ghiassi, R Birke, L Y. Chen
Proceedings of the 2021 IEEE/ACM 8th International Conference on Big Data …, 2021
42021
Labelnet: Recovering noisy labels
A Ghiassi, R Birke, R Han, LY Chen
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
42021
Multi label loss correction against missing and corrupted labels
A Ghiassi, R Birke, LY Chen
Asian Conference on Machine Learning, 359-374, 2023
22023
LABNET: A Collaborative Method for DNN Training and Label Aggregation.
A Ghiassi, R Birke, LY Chen
ICAART (2), 56-66, 2022
22022
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators
C Octavian Pene, A Ghiassi, T Younesian, R Birke, LY Chen
arXiv e-prints, arXiv: 2108.02032, 2021
2*2021
End-to-end learning from noisy crowd to supervised machine learning models
T Younesian, C Hong, A Ghiassi, R Birke, LY Chen
2020 IEEE Second International Conference on Cognitive Machine Intelligence …, 2020
22020
Expertnet: Adversarial learning and recovery against noisy labels
A Ghiassi, R Birke, R Han, LY Chen
arXiv preprint arXiv:2007.05305, 2020
12020
Robust Learning via Golden Symmetric Loss of (un) Trusted Labels
A Ghiassi, R Birke, LY Chen
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023
2023
Artifact: Masa: Responsive Multi-DNN Inference on the Edge
B Cox, J Galjaard, A Ghiassi, R Birke, LY Chen
2021 IEEE International Conference on Pervasive Computing and Communications …, 2021
2021
Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation
M Hadadian Nejad Yousefi, A Ghiassi, B Sadat Hashemi, M Goudarzi
arXiv e-prints, arXiv: 2003.02820, 2020
2020
Conference Opening Session 1-Pervasive computing at the edge
B Cox, JM Galjaard, A Ghiassi, R Birke, H Oikawa, M Kondo
The system can't perform the operation now. Try again later.
Articles 1–18