LSVC: A Lifelong Learning Approach for Stream-View Clustering.

Multiview clustering (MVC) can achieve more accurate results by utilizing complementary information from multiple perspectives, compared to traditional single-view methods. However, current multiview techniques require all views to be available upfront, making them inadequate for dealing with prevalent data sources that arrive as streams, such as stem cell analysis and multicamera surveillance. To address this problem, in this article, we propose a method called lifelong stream-view clustering (LSVC), which comprises an embedding anchor knowledge library and three key components, enabling the capability to perform asynchronous clustering on stream views.

Health poverty alleviation in China from the perspective of historical institutionalism: policy changes and driving factors.

Health poverty alleviation is an effective tool for improving the living quality and developmental conditions of impoverished populations. Since 1978, China has been actively implementing health poverty alleviation projects, resulting in a more robust rural healthcare service network and increased convenience for the local population to access medical treatment. However, it is crucial to acknowledge that China still faces a complex situation with the simultaneous existence of multiple disease threats and the interweaving of various health influencing factors.

One-Stage Shifted Laplacian Refining for Multiple Kernel Clustering.

Graph learning can effectively characterize the similarity structure of sample pairs, hence multiple kernel clustering based on graph learning (MKC-GL) achieves promising results on nonlinear clustering tasks. However, previous methods confine to a "three-stage" scheme, that is, affinity graph learning, Laplacian construction, and clustering indicator extracting, which results in the information distortion in the step alternating. Meanwhile, the energy of Laplacian reconstruction and the necessary cluster information cannot be preserved simultaneously.