4 papers
Semi-Supervised Hyperbolic Hierarchical Clustering with Set-Level Structural Priors
Junjing Zheng, Xinyu Zhang, Xiangfeng Qiu +2
Semi-supervised hierarchical clustering aims to learn a tree structure consistent with data patterns and user-provided supervision. Supervision is usually given as leaf-level relat…
Mode-Aware Non-Linear Tucker Autoencoder for Tensor-based Unsupervised Learning
Junjing Zheng, Chengliang Song, Weidong Jiang +1
High-dimensional data, particularly in the form of high-order tensors, presents a major challenge in self-supervised learning. While MLP-based autoencoders (AE) are commonly employ…
Orientation-Aware Sparse Tensor PCA for Efficient Unsupervised Feature Selection
Junjing Zheng, Xinyu Zhang, Weidong Jiang +2
Recently, introducing Tensor Decomposition (TD) techniques into unsupervised feature selection (UFS) has been an emerging research topic. A tensor structure is beneficial for minin…
Fast Sparse PCA via Positive Semidefinite Projection for Unsupervised Feature Selection
Junjing Zheng, Xinyu Zhang, Yongxiang Liu +3
In the field of unsupervised feature selection, sparse principal component analysis (SPCA) methods have attracted more and more attention recently. Compared to spectral-based metho…