Mathur, Akhil

Flower: A Friendly Federated Learning Research Framework

Beutel, D. J., Topal, T., Mathur, A., Qiu, X., Fernandez-Marques, J., Gao, Y., Sani, L., Li, K. H., Parcollet, T., de Gusmão, P. P. B., et al. (2020) · arXiv

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 622

The Llama 3 Herd of Models

Grattafiori, A., Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Vaughan, A., et al. (2024) · arXiv

Fault Detection and Control SystemsAnomaly Detection Techniques and Applications

Cited by 505

DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware

Mathur, A., Lane, N. D., Bhattacharya, S., Boran, A., Forlivesi, C., & Kawsar, F. (2017) · Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 128

ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition

Jain, Y., Tang, C. I., Min, C., Kawsar, F., & Mathur, A. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 113

Using Deep Data Augmentation Training to Address Software and Hardware Heterogeneities in Wearable and Smartphone Sensing Devices

Mathur, A., Zhang, T., Bhattacharya, S., Velickovic, P., Joffe, L., Lane, N. D., Kawsar, F., & Lio, P. (2018) · 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

Context-Aware Activity Recognition SystemsMobile Crowdsensing and Crowdsourcing

Cited by 70

On-device Federated Learning with Flower

Mathur, A., Beutel, D. J., de Gusmão, P. P. B., Fernandez-Marques, J., Topal, T., Qiu, X., Parcollet, T., Gao, Y., & Lane, N. D. (2021) · arXiv

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 22