Internet of Things

Internet of Things (IoT) represents a paradigm shift from the traditional Internet and Cloud computing to a new reality where all “things” are connected to the Internet. Indeed, it has been estimated that the number of connected IoT-devices will reach one trillion by 2035. Such an explosive growth in IoT-devices necessitates new breakthroughs in AI research that can help efficiently deploy intelligence at the edge. Given that IoT-devices are extremely resource-constrained (e.g., small memory, low operating frequencies for energy efficiency), we focus primarily on challenges related to enabling deeplearning models at the edge.

internet of things

Selected Publications

10 entries « 1 of 2 »

Li, Guihong; Bhardwaj, Kartikeya; Yang, Yuedong; Marculescu, Radu

TIPS: Topologically Important Path Sampling for Anytime Neural Networks Conference

International Conference on Machine Learning (ICML), 2023.

Links | BibTeX

Munir, Mustafa; Avery, William; Marculescu, Radu

MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications Conference

Mobile AI Workshop (Conference on Computer Vision and Pattern Recognition Workshops), 2023.

BibTeX

Farcas, Allen-Jasmin; Marculescu, Radu

Demo Abstract: A Hardware Prototype Targeting Federated Learning with User Mobility and Device Heterogeneity Conference

International Conference on Internet-of-Things Design and Implementation (IoTDI), 2023.

BibTeX

Farcas, Allen-Jasmin; Lee, Myungjin; Kompella, Ramana Rao; Latapie, Hugo; de Veciana, Gustavo; Marculescu, Radu

MOHAWK: Mobility and Heterogeneity-Aware Dynamic Community Selection for Hierarchical Federated Learning Conference

International Conference on Internet-of-Things Design and Implementation (IoTDI), 2023.

Links | BibTeX

Yang, Yuedong; Li, Guihong; Marculescu, Radu

Efficient On-device Training via Gradient Filtering Conference

The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Links | BibTeX

Farcas, Allen-Jasmin; Chen, Xiaohan; Wang, Zhangyang; Marculescu, Radu

Model Elasticity for Hardware Heterogeneity in Federated Learning Systems Proceedings Article

In: Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network (FedEdge), pp. 19-24, 2022.

Links | BibTeX

10 entries « 1 of 2 »