Robust (Deep) Learning Framework Against Dirty Labels and Beyond. - Amirmasoud Ghiassi; Taraneh Younesian; Zilong Zhao 001; Robert Birke; Valerio Schiavoni; Lydia Y. Chen (TPS-ISA, 2019)

End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models. - Taraneh Younesian; Chi Hong; Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (CogMI, 2020)

QActor: On-line Active Learning for Noisy Labeled Stream Data. - Taraneh Younesian; Zilong Zhao 001; Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (CoRR, 2020)

Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation. - Mostafa Hadadian Nejad Yousefi; Amirmasoud Ghiassi; Boshra Sadat Hashemi; Maziar Goudarzi (CoRR, 2020)

ExpertNet: Adversarial Learning and Recovery Against Noisy Labels. - Amirmasoud Ghiassi; Robert Birke; Rui Han 001; Lydia Y. Chen (CoRR, 2020)

TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. - Amirmasoud Ghiassi; Taraneh Younesian; Robert Birke; Lydia Y. Chen (CoRR, 2020)

QActor: Active Learning on Noisy Labels. - Taraneh Younesian; Zilong Zhao 001; Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (ACML, 2021)

TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. - Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (BDCAT, 2021)

LABELNET: Recovering Noisy Labels. - Amirmasoud Ghiassi; Robert Birke; Rui Han 001; Lydia Y. Chen (IJCNN, 2021)

Artifact: Masa: Responsive Multi-DNN Inference on the Edge. - Bart Cox; Jeroen Galjaard; Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (PerCom Workshops, 2021)

Masa: Responsive Multi-DNN Inference on the Edge. - Bart Cox; Jeroen Galjaard; Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (PerCom, 2021)

MemA: Fast Inference of Multiple Deep Models. - Jeroen Galjaard; Bart Cox; Amirmasoud Ghiassi; Lydia Y. Chen; Robert Birke (PerCom Workshops, 2021)

Online Label Aggregation: A Variational Bayesian Approach. - Chi Hong; Amirmasoud Ghiassi; Yichi Zhou; Robert Birke; Lydia Y. Chen (WWW, 2021)

Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators. - Cosmin Octavian Pene; Amirmasoud Ghiassi; Taraneh Younesian; Robert Birke; Lydia Y. Chen (CoRR, 2021)

Multi Label Loss Correction against Missing and Corrupted Labels. - Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (ACML, 2022)

Trusted Loss Correction for Noisy Multi-Label Learning. - Amirmasoud Ghiassi; Cosmin Octavian Pene; Robert Birke; Lydia Y. Chen (ACML, 2022)

LABNET: A Collaborative Method for DNN Training and Label Aggregation. - Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (ICAART (2), 2022)

Robust Learning via Golden Symmetric Loss of (un)Trusted Labels. - Amirmasoud Ghiassi; Robert Birke; Lydia Y. Chen (SDM, 2023)