3 accepted papers
Federated Learning (FL) has emerged as a promising approach for distributed machine learning, enabling clients to collaboratively train models without sharing their data. However, existing FL methods continue to face challenges when dealing with non-IID data, particularly under conditions of extreme…
Class imbalance is a prevalent issue in real-world graph-structure data, such as social and citation networks, posing significant challenges for Graph Neural Networks (GNNs). Existing solutions often focus on balancing class distributions via oversampling techniques, which may lead to overfitting an…
Symbolic Regression of Integer Sequences (SRIS) aims to discover precise mathematical formulas from integer sequences. The neural machine translation-based method of SRIS trains the model using randomly generated data, and directly utilizes the trained model for inference on target sequences. Howeve…