Self-renewal machine learning approach for fast wireless network optimization
The throughput maximization in multi-hop wireless networks is largely limited by interference
due to the reuse of the channel resources. Although machine learning (ML) can accelerate …
due to the reuse of the channel resources. Although machine learning (ML) can accelerate …
On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study
This paper demonstrates the potential of vibration-based Foundation Models (FMs), pre-
trained with unlabeled sensing data, to improve the robustness of run-time inference in (a …
trained with unlabeled sensing data, to improve the robustness of run-time inference in (a …
VibroFM: Towards Micro Foundation Models for Robust Multimodal IoT Sensing
The paper argues for the feasibility and utility of micro foundation models (µFMs), a key
direction for future smart IoT/CPS systems that exploits advances in self-supervised …
direction for future smart IoT/CPS systems that exploits advances in self-supervised …
Machine Learning Assisted Capacity Optimization for B5G/6G Integrated Access and Backhaul Networks
The cross-layer design on the routing of traffic and scheduling of wireless backhaul links in
the beyond 5G (B5G)/6G integrated access and backhaul (IAB) networks has continued to …
the beyond 5G (B5G)/6G integrated access and backhaul (IAB) networks has continued to …
[PDF][PDF] AutoWatch: Learning Driver Behavior with Graphs for Auto Theft Detection and Situational Awareness
Millions of lives are lost due to road accidents each year, emphasizing the importance of
improving driver safety measures. In addition, physical vehicle security is a persistent …
improving driver safety measures. In addition, physical vehicle security is a persistent …