Clustering and Unsupervised Learning
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h-DBSCAN: A simple fast DBSCAN algorithm for big data
邵源 翁 (华侨大学)*; Jin Gou (College of Computer Science and Technology, Huaqiao University, Xiamen, China) -
Multiple Partitions Alignment via Spectral Rotation
Shudong Huang (Sichuan University)*; Ivor Tsang (University of Technology Sydney); Zenglin Xu (Harbin Institute of Technology); Jiancheng Lv (Sichuan University) -
Multi-view Latent Subspace Clustering based on both Global and Local Structure
honghan zhou (nanjing normal university); Weiling Cai (Nanjing Normal University)*; LE Xu ( Nanjing Normal University) -
Deep Structural Contrastive Subspace Clustering
Bo Peng (The University of Queensland); Wenjie Zhu (China Jiliang University)* -
Scaling Average-Linkage via Sparse Cluster Embeddings
Thomas Lavastida (Carnegie Mellon University)*; Kefu Lu (Washington and Lee University); Benjamin Moseley (Carnegie Mellon University); Yuyan Wang (Carnegie Mellon University) -
Unsupervised cycle-consistent network for removing susceptibility artifacts in single-shot EPI
Weida Xie (Wuhan University of Technology)*; 适 陈 (Wuhan University of Technology); Qingjia Bao (Chinese Academy of Sciences); 可文 刘 (Wuhan University of Technology); Zhao Li (State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Math, Innovation Academy for Precision Measurement Science and Technology. ); Chongxin Bai (Wuhan University of Technology); Otikovs Martins (Weizmann Institute of Science, Rehovot, 76001); Piqiang Li (Wuhan University of Technology); Jie Wang (Chinese Academy of Sciences) -
Contrastive Neural Processes for Self-Supervised Learning
Konstantinos Kallidromitis (Panasonic)*; Denis A Gudovskiy (Panasonic); Kazuki Kozuka (Panasonic Corporation); Iku Ohama (Panasonic); Luca Rigazio (Panasonic)