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Amirmasoud Ghiassi
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2020 – today
- 2023
- [c13]Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
Robust Learning via Golden Symmetric Loss of (un)Trusted Labels. SDM 2023: 568-576 - 2022
- [c12]Amirmasoud Ghiassi, Cosmin Octavian Pene, Robert Birke, Lydia Y. Chen:
Trusted Loss Correction for Noisy Multi-Label Learning. ACML 2022: 343-358 - [c11]Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
Multi Label Loss Correction against Missing and Corrupted Labels. ACML 2022: 359-374 - [c10]Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
LABNET: A Collaborative Method for DNN Training and Label Aggregation. ICAART (2) 2022: 56-66 - 2021
- [c9]Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
QActor: Active Learning on Noisy Labels. ACML 2021: 548-563 - [c8]Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. BDCAT 2021: 52-62 - [c7]Amirmasoud Ghiassi, Robert Birke, Rui Han, Lydia Y. Chen:
LABELNET: Recovering Noisy Labels. IJCNN 2021: 1-8 - [c6]Bart Cox
, Jeroen Galjaard, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
Masa: Responsive Multi-DNN Inference on the Edge. PerCom 2021: 1-10 - [c5]Jeroen Galjaard, Bart Cox
MemA: Fast Inference of Multiple Deep Models. PerCom Workshops 2021: 281-286 - [c4]Bart Cox
Artifact: Masa: Responsive Multi-DNN Inference on the Edge. PerCom Workshops 2021: 446-447 - [c3]Chi Hong, Amirmasoud Ghiassi, Yichi Zhou, Robert Birke, Lydia Y. Chen:
Online Label Aggregation: A Variational Bayesian Approach. WWW 2021: 1904-1915 - [i6]Cosmin Octavian Pene, Amirmasoud Ghiassi, Taraneh Younesian, Robert Birke, Lydia Y. Chen:
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators. CoRR abs/2108.02032 (2021) - 2020
- [c2]Taraneh Younesian, Chi Hong, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models. CogMI 2020: 17-26 - [i5]Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
QActor: On-line Active Learning for Noisy Labeled Stream Data. CoRR abs/2001.10399 (2020) - [i4]Mostafa Hadadian Nejad Yousefi
Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation. CoRR abs/2003.02820 (2020) - [i3]Amirmasoud Ghiassi, Robert Birke, Rui Han, Lydia Y. Chen:
ExpertNet: Adversarial Learning and Recovery Against Noisy Labels. CoRR abs/2007.05305 (2020) - [i2]Amirmasoud Ghiassi, Taraneh Younesian, Robert Birke, Lydia Y. Chen:
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. CoRR abs/2007.06324 (2020) - [i1]Taraneh Younesian, Chi Hong, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models. CoRR abs/2011.06833 (2020)
2010 – 2019
- 2019
- [c1]Amirmasoud Ghiassi, Taraneh Younesian, Zilong Zhao, Robert Birke, Valerio Schiavoni
Robust (Deep) Learning Framework Against Dirty Labels and Beyond. TPS-ISA 2019: 236-244
Coauthor Index
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