Mahsa Mozaffari

According to our database, Mahsa Mozaffari authored at least 10 papers between 2019 and 2025.

Collaborative distances:

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

2025

GLEN: Generalized Focal Loss Ensemble of Low-Rank Networks for Calibrated Visual Question Answering.

Mahsa Mozaffari, Hitesh Sapkota, Qi Yu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Enhancing GANs With MMD Neural Architecture Search, PMish Activation Function, and Adaptive Rank Decomposition.

Prasanna Reddy Pulakurthi, Mahsa Mozaffari, Sohail A. Dianat, Jamison Heard, Raghuveer M. Rao, Majid Rabbani

IEEE Access, 2024

Enhancing GAN Performance Through Neural Architecture Search and Tensor Decomposition.

Prasanna Reddy Pulakurthi, Mahsa Mozaffari, Sohail A. Dianat, Majid Rabbani, Jamison Heard, Raghuveer Rao

Proceedings of the IEEE International Conference on Acoustics, 2024

2022

Online Multivariate Anomaly Detection and Localization for High-Dimensional Settings.

Mahsa Mozaffari, Keval Doshi, Yasin Yilmaz

Sensors, 2022

Real-Time Detection and Classification of Power Quality Disturbances.

Mahsa Mozaffari, Keval Doshi, Yasin Yilmaz

Sensors, 2022

2021

Improved L1-Tucker via L1-Fitting.

Mahsa Mozaffari, Panos P. Markopoulos, Ashley Prater-Bennette

Proceedings of the 29th European Signal Processing Conference, 2021

Robust Barron-Loss Tucker Tensor Decomposition.

Mahsa Mozaffari, Panos P. Markopoulos

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2019

Online Multivariate Anomaly Detection and Localization for High-dimensional Settings.

Mahsa Mozaffari, Yasin Yilmaz

CoRR, 2019

RAPID: Real-time Anomaly-based Preventive Intrusion Detection.

Keval Doshi, Mahsa Mozaffari, Yasin Yilmaz

Proceedings of the ACM Workshop on Wireless Security and Machine Learning, 2019

Online Anomaly Detection in Multivariate Settings.

Mahsa Mozaffari, Yasin Yilmaz

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019