Abstract: In this paper, we present a probability graph-based semantic information compression system for scenarios where the base station (BS) and the user share common background knowledge. We ...
This repository contains the appendix, code, and data for the paper "Edge Probability Graph Models Beyond Edge Independency" published in the IEEE International Conference on Data Mining (ICDM) 2025.
This package includes a module for generating random graph without a forbidden constraint. This software requires Java 6 (JDK 1.6.0+). (You must have installed it ...
Aim and Objective: Sequence analysis is one of the foundations in bioinformatics. It is widely used to find out the feature metrics hidden in the sequence. Otherwise, the graphical representation of ...
In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed.
A set of independence statements may define the independence structure of interest in a family of joint probability distributions. This structure is often captured by a graph that consists of nodes ...
Reward shaping using directed graph convolution neural networks for reinforcement learning and games
Over the past few decades, game theory has utilized the concepts and methods of reinforcement learning (RL) to solve decision-making problems [1]; [2]; [3]. An RL problem can be seen as a game between ...
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