AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
82 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This paper introduces a novel graph theory reasoning framework based on adaptive neural networks. Traditional graph theory reasoning methods often rely on fixed models, limiting their effectiveness in complex graph problems. Our proposed approach leverages adaptive neural networks to address these limitations, offering...
This paper introduces a novel approach to topology analysis utilizing graph neural networks (GNNs). We propose a method for automatically constructing and analyzing complex topology graphs, with the capability to predict and optimize topological structures. Traditional approaches rely on manual graph construction, whic...
This paper introduces a novel machine learning algorithm, termed the Dynamic Graph-Based Machine Learning Algorithm, designed to enhance the performance of graph neural networks (GNNs) through adaptive graph structure learning. Traditional GNN approaches often rely on pre-defined graph structures, limiting their applic...
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data without directly exchanging the data itself. However, FL systems are vulnerable to Byzantine attacks, where malicious participants introduce corrupted data or models to compromise the learning process. This pap...
This paper explores a novel approach to contextual reasoning by leveraging multi-modal embeddings. The core idea is to learn deep embeddings from diverse data modalities – including text, images, and audio – and subsequently establish contextual relationships between them. We propose a framework that utilizes multi-mod...
This paper proposes a novel approach to program vulnerability prediction by leveraging knowledge graphs. The core idea is to construct a program vulnerability knowledge graph, integrating code semantics and vulnerability data. We utilize Graph Neural Networks (GNNs) to analyze the relationships between code and vulnera...
This paper addresses the limitations of traditional knowledge graph reasoning, which primarily relies on correlational relationships, leading to potentially biased inferences. We propose a novel approach to multi-modal knowledge graph reasoning by explicitly modeling causal relationships between entities. Our core clai...
Dynamic topology generation is a fundamental challenge in network design, crucial for applications ranging from computer networks to biological systems. This paper investigates the application of graph neural networks (GNNs) to automate the creation of complex network topologies, offering a paradigm shift from manual d...
This paper introduces a novel adaptive graph neural network (GNN) architecture designed specifically for high-dimensional data. Traditional GNNs often struggle with the complexity of high-dimensional data, leading to slow convergence and suboptimal performance. This work proposes a dynamically adjustable graph structur...
This paper investigates the application of Graph Convolutional Neural Networks (GCNs) for social network sentiment analysis. Traditional methods for analyzing public opinion often struggle with the complex, interconnected nature of social networks and the dynamic patterns of information dissemination. This research pro...
This paper introduces a novel approach to feature selection based on adaptive graph theory reasoning. Traditional feature selection methods often rely on static models, limiting their effectiveness in complex graph-based problems. We propose a framework leveraging the adaptive nature of graph structures and parameters...
This paper proposes a novel approach to program vulnerability prediction by leveraging knowledge graphs. The core idea is to construct a program vulnerability knowledge graph, integrating code semantics and vulnerability data. We utilize Graph Neural Networks (GNNs) to analyze the relationships between code and vulnera...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.