Amirmasoud Ghiassi

According to our database, Amirmasoud Ghiassi authored at least 18 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Robust Learning via Golden Symmetric Loss of (un)Trusted Labels.

Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

2022

LABNET: A Collaborative Method for DNN Training and Label Aggregation.

Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

Trusted Loss Correction for Noisy Multi-Label Learning.

Amirmasoud Ghiassi, Cosmin Octavian Pene, Robert Birke, Lydia Y. Chen

Proceedings of the Asian Conference on Machine Learning, 2022

Multi Label Loss Correction against Missing and Corrupted Labels.

Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the Asian Conference on Machine Learning, 2022

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

Online Label Aggregation: A Variational Bayesian Approach.

Chi Hong, Amirmasoud Ghiassi, Yichi Zhou, Robert Birke, Lydia Y. Chen

Proceedings of the WWW '21: The Web Conference 2021, 2021

MemA: Fast Inference of Multiple Deep Models.

Jeroen Galjaard, Bart Cox, Amirmasoud Ghiassi, Lydia Y. Chen, Robert Birke

Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2021

Masa: Responsive Multi-DNN Inference on the Edge.

Bart Cox, Jeroen Galjaard, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications, 2021

Artifact: Masa: Responsive Multi-DNN Inference on the Edge.

Bart Cox, Jeroen Galjaard, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2021

LABELNET: Recovering Noisy Labels.

Amirmasoud Ghiassi, Robert Birke, Rui Han, Lydia Y. Chen

Proceedings of the International Joint Conference on Neural Networks, 2021

TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise.

Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the BDCAT '21: 2021 IEEE/ACM 8th International Conference on Big Data Computing, Applications and Technologies, Leicester, United Kingdom, December 6, 2021

QActor: Active Learning on Noisy Labels.

Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the Asian Conference on Machine Learning, 2021

2020

TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise.

Amirmasoud Ghiassi, Taraneh Younesian, Robert Birke, Lydia Y. Chen

CoRR, 2020

ExpertNet: Adversarial Learning and Recovery Against Noisy Labels.

Amirmasoud Ghiassi, Robert Birke, Rui Han, 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

QActor: On-line Active Learning for Noisy Labeled Stream Data.

Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

CoRR, 2020

End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models.

Taraneh Younesian, Chi Hong, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen

Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020

2019

Robust (Deep) Learning Framework Against Dirty Labels and Beyond.

Amirmasoud Ghiassi, Taraneh Younesian, Zilong Zhao, Robert Birke, Valerio Schiavoni, Lydia Y. Chen

Proceedings of the First IEEE International Conference on Trust, 2019