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Stochastic model-driven capacity planning framework for multi-access edge computing
Frontiers Deep Reinforcement Learning Based Resource Allocation Strategy in Cloud-Edge Computing System
PDF) Stochastic Model Driven Performance and Availability Planning
Energy-efficient task offloading strategy in mobile edge computing for resource-intensive mobile applications - ScienceDirect
A Quantization Framework for Bayesian Deep Learning
The VIMMJIPDA: Multi-target tracker with multiple models and visibility
Research - UCI IASL
Midwest Integrated Center for Computational Materials - Publications
Chapter 12 Simulation-based Scheduling in Industry 4.0 Simio and Simulation - Modeling, Analysis, Applications - 6th Edition
Minimize average tasks processing time in satellite mobile edge computing systems via a deep reinforcement learning method, Journal of Cloud Computing
CHAPTER 1 Department of Defense Decision Support Systems
PDF] Stochastic Model Driven Performance and Availability Planning for a Mobile Edge Computing System
PDF) Stochastic Model Driven Performance and Availability Planning
Stochastic model-driven capacity planning framework for multi-access edge computing
A computer architecture based on disruptive information technologies for drug management in hospitals [PeerJ]