Search Results for author:
Found 6 papers, 1 papers with code
EmoDM: A Diffusion Model for Evolutionary Multi-objective Optimization
Evolutionary algorithms have been successful in solving multi-objective optimization problems (MOPs).
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems
It has been shown that learning-based methods outperform traditional heuristics and mathematical solvers on the Traveling Salesman Problem (TSP) in terms of both performance and computational efficiency.
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Knowledge tracing (KT) aims to trace students' knowledge states by predicting whether students answer correctly on exercises.
Augmented Transformers with Adaptive n-grams Embedding for Multilingual Scene Text Recognition
While vision transformers have been highly successful in improving the performance in image-based tasks, not much work has been reported on applying transformers to multilingual scene text recognition due to the complexities in the visual appearance of multilingual texts.
A Graph Neural Network with Negative Message Passing for Graph Coloring
In this paper, we propose a graph network model for graph coloring, which is a class of representative heterophilous problems.
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location
The network outputs are then converted into the probability distribution of the Pareto set, from which a set of non-dominated solutions can be sampled non-autoregressively.
