Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies
The emergence of 5G and edge computing hardware has brought about a significant shift in
artificial intelligence, with edge AI becoming a crucial technology for enabling intelligent …
artificial intelligence, with edge AI becoming a crucial technology for enabling intelligent …
Cooperative Multi-Agent Deep Reinforcement Learning for Dynamic Task Execution and Resource Allocation in Vehicular Edge Computing
Computer vision plays a crucial role in enabling connected autonomous vehicles (CAVs) to
observe and comprehend their surroundings. The computer vision tasks are typically based …
observe and comprehend their surroundings. The computer vision tasks are typically based …
DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads
Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and drone control
involve dynamic behaviors in various granularity; task, model, and layers within a model …
involve dynamic behaviors in various granularity; task, model, and layers within a model …
HILT: Personalized and Adaptive Privacy-Aware Early-Exit for Reinforcement Learning in Human-in-the-Loop Systems
Reinforcement Learning (RL) has increasingly become a preferred method over traditional
rule-based systems in diverse human-in-the-loop (HITL) applications due to its adaptability …
rule-based systems in diverse human-in-the-loop (HITL) applications due to its adaptability …