2 papers
cs.LG2026
Federated Hash Projected Latent Factor Learning
Jialan He
Hash Learning (HL) is an efficient representation learning approach that maps real-valued data into compact binary representations. Traditional HL methods typically require users t…
cs.LG2026
Hyperparameter Learning for Latent Factorization of Tensors for Representation Learning to Large-scale Dynamic Weighted Directed Network
Yaqian Zhan, Jialan He, Tianzhu Chen
Large-scale dynamic weighted directed networks (DWDNs) are widely used to model time-varying interactions among nodes. Latent factorization of tensors (LFT) extracts target knowled…