: On-Device Real-Time Deep Reinforcement Learning for Autonomous Robotics

Z Li, A Samanta, Y Li, A Soltoggio… - 2023 IEEE Real-Time …, 2023 - ieeexplore.ieee.org
Autonomous robotic systems, like autonomous vehicles and robotic search and rescue,
require efficient on-device training for continuous adaptation of Deep Reinforcement …

Red: A systematic real-time scheduling approach for robotic environmental dynamics

Z Li, T Ren, X He, C Liu - 2023 IEEE Real-Time Systems …, 2023 - ieeexplore.ieee.org
Intelligent robots are designed to effectively navigate dynamic and unpredictable
environments laden with moving mechanical elements and objects. Such environment …

IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition

Z Hu, A Radmehr, Y Zhang, S Pan… - Proceedings of the ACM on …, 2024 - dl.acm.org
While occlusal diseases-the main cause of tooth loss--significantly impact patients' teeth and
well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing …

Genie: Smart ROS-based Caching for Connected Autonomous Robots

Z Li, S Bateni, C Liu - arXiv preprint arXiv:2402.19410, 2024 - arxiv.org
Despite the promising future of autonomous robots, several key issues currently remain that
can lead to compromised performance and safety. One such issue is latency, where we find …

Distantly-Supervised Joint Entity and Relation Extraction with Noise-Robust Learning

Y Li, X Yu, Y Guo, Y Liu, H Chen, C Liu - arXiv preprint arXiv:2310.04994, 2023 - arxiv.org
Joint entity and relation extraction is a process that identifies entity pairs and their relations
using a single model. We focus on the problem of training these models on distantly-labeled …