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06/11/2023
Deep Demixing: Reconstructing the Evolution of Network Epidemics
We propose the deep demixing (DDmix) model, a graph autoencoder that can...
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04/30/2023
Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian
We propose a flexible framework for defining the 1-Laplacian of a hyperg...
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04/18/2023
Learning to Transmit with Provable Guarantees in Wireless Federated Learning
We propose a novel data-driven approach to allocate transmit power for f...
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01/27/2022
Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks
We develop a novel graph-based trainable framework to maximize the weigh...
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11/15/2021
Power Allocation for Wireless Federated Learning using Graph Neural Networks
We propose a data-driven approach for power allocation in the context of...
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02/19/2021
Co-clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning
We propose a novel method to co-cluster the vertices and hyperedges of h...
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03/18/2019
POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
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02/28/2019