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Projection Clustering Support Vector Machine for semi-supervised learning
DOI:10.1016/j.patcog.2026.114739.png)
摘要
En 中文
我们提出投影聚类支持向量机(PCSVM),它统一了边界最大化、聚类和投影学习。
基于温度的软聚类被用于捕捉未标记数据的内在结构。
我们设计了一种双一致性伪标签机制以抑制噪声传播。
Keyword:
Semi-supervised learning
Support vector machine
Clustering consistency
Discriminative projection
Pseudo-labeling
期刊
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
Optimization meets machine learning: an exact algorithm for semi-supervised support vector machines优化与机器学习:半监督支持向量机的精确算法
Learnable Subspace Orthogonal Projection for Semi-supervised Image Classification可学习的子空间正交投影用于半监督图像分类
Semi-supervised sparse least squares support vector machine based on Mahalanobis distance
APPLIED INTELLIGENCE
IF3.5
Conditional Consistency Regularization for Semi-Supervised Multi-Label Image Classification半监督多标签图像分类的条件一致性正则化

