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Found 8 papers, 0 papers with code
Meta Reinforcement Learning for Multi-Task Offloading in Vehicular Edge Computing
The objective is to design a unified solution to minimize task execution time under different MTO scenarios.
Rethinking Attention Mechanism in Time Series Classification
Attention-based models have been widely used in many areas, such as computer vision and natural language processing.
On Jointly Optimizing Partial Offloading and SFC Mapping: A Cooperative Dual-agent Deep Reinforcement Learning Approach
Mobile devices (MDs) can offload computation-intensive applications, which can be represented by SFCs, fully or partially to MEC servers for remote execution.
Evolutionary Multi-Objective Reinforcement Learning Based Trajectory Control and Task Offloading in UAV-Assisted Mobile Edge Computing
This paper adapts the evolutionary multi-objective RL (EMORL), a multi-policy multi-objective RL, to the TCTO problem.
An Efficient Federated Distillation Learning System for Multi-task Time Series Classification
For each connected user, its student model's hidden layers' weights are uploaded to the EFDLS server periodically.
RTFN: A Robust Temporal Feature Network for Time Series Classification
Most of the existing feature networks pay more attention to local features rather than the relationships among them.
RTFN: Robust Temporal Feature Network
The temporal feature networks are built to extract basic features from input data while the attentional LSTM networks are devised to capture complicated shapelets and relationships to enrich features.
STDPG: A Spatio-Temporal Deterministic Policy Gradient Agent for Dynamic Routing in SDN
Dynamic routing in software-defined networking (SDN) can be viewed as a centralized decision-making problem.
