ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Introduction: Recently, federated learning has been successfully applied in fields related to cyber-physical-social systems (CPSSs), owing to its ability to harness decentralized clients for training ...
Graph Neural Networks (GNNs) have emerged as a dominant framework for semi-supervised learning on graph-structured data, achieving remarkable performance in tasks such as node classification through ...
Class imbalance remains a critical challenge in semi-supervised learning (SSL), especially when distributional mismatches between labeled and unlabeled data lead to biased classification. Although ...
Abstract: As a compromise between supervised and unsupervised learning, semi-supervised learning (SSL) harnesses both labeled and unlabeled data to enhance learning performance. Graph-based ...
Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric’s capacity to power ...
Automatic classification of interior decoration styles has great potential to guide and streamline the design process. Despite recent advancements, it remains challenging to construct an accurate ...
. ├─ code/ │ ├─ feature_selection_lasso.py │ ├─ key_sample_three_sim.py │ ├─ key_sample_three_sim_filtered.py │ ├─ semi_three_sim.py ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
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