ShenYanUSC

Computer Science Ph.D. student at USC.

Pinned Repositories

Fair_Class_Balancing
This repository contains a sample implementation of Fair Class Balancing. For more information, see our paper Fair Class Balancing: Enhancing Model Fairness without Observing Sensitive Attributes published on CIKM 2020.
Language:Python0 2 01
FedML
A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)
Language:Python00
MLFA
Multi-Layer Factor Analysis. This repository contains a sample implementation of Multi-Layer Factor Analysis, which provides a method to identify heterogeneous behavior patterns. For more information, see our paper Mitigating the Bias of Heterogeneous Human Behavior in Affective Computing published on ACII 2021
Language:Python00
Multimodal_Fairness
This repository contains a sample implementation of two debiasing methods: data balancing and adversarial fairness. For more information, see our paper Mitigating Biases in Multimodal Personality Assessment published on ICMI 2020.
Language:Jupyter Notebook20

ShenYanUSC/Multimodal_Fairness
This repository contains a sample implementation of two debiasing methods: data balancing and adversarial fairness. For more information, see our paper Mitigating Biases in Multimodal Personality Assessment published on ICMI 2020.
Language:Jupyter Notebook20
ShenYanUSC/Fair_Class_Balancing
This repository contains a sample implementation of Fair Class Balancing. For more information, see our paper Fair Class Balancing: Enhancing Model Fairness without Observing Sensitive Attributes published on CIKM 2020.
Language:Python0 2 01
ShenYanUSC/FedML
A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)
Language:Python00
ShenYanUSC/MLFA
Multi-Layer Factor Analysis. This repository contains a sample implementation of Multi-Layer Factor Analysis, which provides a method to identify heterogeneous behavior patterns. For more information, see our paper Mitigating the Bias of Heterogeneous Human Behavior in Affective Computing published on ACII 2021
Language:Python00