Support vector machine (SVM) is widely recognized as an effective classification tool and
has demonstrated superior performance in diverse applications. However, for large-scale …

Semi-supervised learning has become a hot learning framework, where large amounts of
unlabeled data and small amounts of labeled data are available during the training process …

For supervised regression tasks we propose and study a new tool, namely Kriging Estimator
based on the Partition of Unity (KEPU) method. Its background belongs to the framework of …

The generalization performance of “All-in-one” Multi-class SVM (AIO-MSVM) based on
uniformly ergodic Markovian chain (ueMc) samples is considered. We establish the fast …

Hybrid learning is an excellent method that combines the global information of data with the
local information of data. Different from the known hybrid learning algorithms, in this paper …

Support vector machine (SVM) is an excellent pattern recognition method. Many
experiments have shown that SVM can achieve a generalization performance gain by …

This article presents a classification method that utilizes impedance spectrum features and
an enhanced K-means algorithm for Lithium-ion batteries. Additionally, a parameter …

In this paper, a truly meshless method based on the partition of unity method (PUM) is
developed for the numerical solution of the two-dimensional forward–backward heat …

Event cameras are neuromorphic sensors that capture asynchronous and sparse event
stream when per-pixel brightness changes. The state-of-the-art processing methods for …

The spatiotemporal correlation of events obtained by event camera contains the operational
laws of moving targets. For deeper understanding events, an effective spatiotemporal …