计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 240100054-7.doi: 10.11896/jsjkx.240100054
杨兴1,3, 王士同2, 胡文军1,3
YANG Xing1,3, WANG Shitong2, HU Wenjun1,3
摘要： 流形学习的核心是通过保持局部结构来捕捉数据中隐藏的几何信息,而局部结构通常利用冗余或干扰的原始数据进行评价,这意味着局部结构是不可靠的,存在局部结构置信度不足的问题。为此,针对性地提出一种局部结构自适应的线性投影方法。该方法的核心在于:一方面,它强制线性投影后的低维表示保持高维空间中的局部结构;另一方面,通过低维空间表示更新高维空间中的局部结构,并通过循环迭代方式实现局部结构的自适应。真实数据集上的实验结果表明,所提方法在各项性能指标上均优于其他对比方法。
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