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Found 8 papers, 0 papers with code
Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetching
The vision of pervasive artificial intelligence (AI) services can be realized by training an AI model on time using real-time data collected by internet of things (IoT) devices.
Mobility-Induced Graph Learning for WiFi Positioning
A smartphone-based user mobility tracking could be effective in finding his/her location, while the unpredictable error therein due to low specification of built-in inertial measurement units (IMUs) rejects its standalone usage but demands the integration to another positioning technique like WiFi positioning.
Towards Semantic Communication Protocols for 6G: From Protocol Learning to Language-Oriented Approaches
neural network-oriented symbolic protocols developed by converting Level 1 MAC outputs into explicit symbols; and Level 3 MAC.
Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communication
In this method, referred to as SL with layer freezing (SLF), each encoder downloads a misaligned decoder, and locally fine-tunes a fraction of these encoder-decoder NN layers.
Enabling AI Quality Control via Feature Hierarchical Edge Inference
Specifically, feature network is designed based on feature hierarchy, a one-directional feature dependency with a different scale.
Towards Semantic Communication Protocols: A Probabilistic Logic Perspective
Classical medium access control (MAC) protocols are interpretable, yet their task-agnostic control signaling messages (CMs) are ill-suited for emerging mission-critical applications.
Communication-Efficient and Personalized Federated Lottery Ticket Learning
The lottery ticket hypothesis (LTH) claims that a deep neural network (i. e., ground network) contains a number of subnetworks (i. e., winning tickets), each of which exhibiting identically accurate inference capability as that of the ground network.
Understanding Uncertainty of Edge Computing: New Principle and Design Approach
Due to the edge's position between the cloud and the users, and the recent surge of deep neural network (DNN) applications, edge computing brings about uncertainties that must be understood separately.
Information Theory Networking and Internet Architecture Information Theory
