Heterogeneous agile Earth observation satellite (AEOS) scheduling requires task selection, satellite assignment, and observation sequencing under satellite-dependent visibility windows, attitude maneuvering requirements, energy consumption, and onboard storage constraints. Since satellites differ in orbital access, man...
The conversational recommendation system (CRS) breaks the limitations of traditional static methods, presenting a novel framework for personalized recommendations with real-time adaptability and dynamic interactions. Existing methods predominantly focus on the balance between ”exploration and exploitation (E&E)”, but t...
Di Jin, Run-Ze Li, Jia-Qi Cui et al.· ACM Transactions on Informat...· 0 citations
This work proposes a novel Granular Envelope Contrastive Learning (GECL) method that explicitly models intra-class variations by generating multiple granular envelopes for each class, and jointly reduces domain discrepancy and enhances feature discriminability.
Pufei Li, Pin Wang, Yongming Li et al.· Neural Networks· 0 citations
A representation-enhanced AD model with prototype learning and neighborhood rough set (ADPLN) is proposed, which outperforms the state-of-the-art methods and designs a sample-prototype correlation objective function to promote the learning of discriminative representations of normals and mitigate the negative impacts o...
Jiao-Long Chen, Ye Liu, Yu-Hua Qian et al.· IEEE Transactions on Cyberne...· 0 citations
A new density-based clustering method called stacked density granulation (SDG) is proposed, which constructs information granularities capable of effectively describing both convex and nonconvex data.
Wen-Tao Li, Xuan-Zhen Zhao, W. Pedrycz et al.· IEEE Transactions on Cyberne...· 0 citations
An incrementally expanding fuzzy neural module network (FNMN) designed to effectively handle both low- and high-dimensional problems without relying on dimensionality reduction techniques is proposed, achieving an average performance improvement compared with a conventional fuzzy clustering-based model across diverse b...
Eun-Hu Kim, Hao Huang, Zheng Wang et al.· IEEE Transactions on Cyberne...· 0 citations
Intrinsic Logit-Based Debiasing (ILBD), a robust post-hoc framework that estimates bias directly from task-relevant data without external dependencies and class priors, and effectively rectifies the classifier's bias directly from the inherent statistical patterns of the training data.
