International Conference on Computer and Knowledge Engineering

Home / 13th International Conference on Computer and Knowledge Engineering

Robust Learning to Learn Graph Topologies

Authors :

Navid Akhavan Attar¹ Ali Fahim²

1- University of Tehran 2- University of Tehran

Keywords :

Network Science،Machine Learning،Graph Learning،Neural Networks،Complex Systems،Learning to Learn Graph Topologies،Graph Topology

Abstract :

Graph learning and revealing the relationship between agents is an essential and pivotal problem in network science and machine learning, carrying significant implications across a broad range of applications. In the literature, there are generally two approaches to graph learning: model-based and learning-based methods. Recent learning-based methods like L2G, GLAD, and uGLAD add more flexibility to model structural priors in graph learning. We propose a novel approach, RL2G, which offers robustness to the “Learning to Learn Graph Topologies” method. This allows us to recover the topologies of graphs using a pre-trained model, independently from their size and topological properties. The experiments conducted on both synthetic and real-world data provide strong evidence that our approach performs well in revealing the relationships between different data entities.

List of archived papers

Deep Learning Based High-Resolution Edge Detection for Microwave Imaging using a Variational Autoencoder

Seyed Reza Razavi Pour - Leila Ahmadi - Amir Ahmad Shishegar

Improving the classification of high dimensional class-imbalanced data using the Chaos particle swarm optimization with Levy Flight

Mohammad Ali Zarif - Javad Hamidzadeh

Financial Market Prediction Using Deep Neural Networks with Hardware Acceleration

Dara Rahmati - Mohammad Hadi Foroughi - Ali Bagherzadeh - Mehdi Foroughi - Saeid Gorgin

Probabilistic Short-Term Load Forecasting Using GBDT-Based Sister Forecasts and Ensemble Methods

Hossein Shahinzadeh - Hamed Nafisi - Amirafshin Zamani - Saiedeh Mehrabani-Najafabadi - Arezou Mahmoudi - Farshad Ebrahimi

Parallel Local Feature Selection For High-dimensional Data

Zhaleh Manbari - Chiman Salavati - Fardin AkhlaghianTab - Barzan Saeedpoor - Himan Delbina - Mahmud Abdulla Mohammad

Solving the influence maximization problem by using entropy and weight of edges

Farzaneh Kazemzadeh - Amir Karian - Mitra Mirzarezaee - Ali Asghar Safaei

Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution

Mohammadreza Sharifi - Danial Ahmadzadeh

Intelligent Adaptive Control of Wheeled Mobile Robots with MLP Neural Networks under Input Constraints

Soheil Sheikh ahmadi - Arash Rahmani

An Attention-Based Model for Clinical Time Series Prediction: Enhancing ICU Readmission Prediction

Hananeh Sadat Madinei - Mohammad Reza Keyvanpour - Seyed Vahab Shojaedini

Extracting Major Topics of COVID-19 Related Tweets

Faezeh Azizi - Hamed Vahdat-Nejad - Hamideh Hajiabadi - Mohammad Hossein Khosravi

more

Samin Hamayesh - Version 44.5.0