20 citations · 75 across the 18 of their papers we have counts for
4 papers · 1 filter
Angular Embedding: A New Angular Robust Principal Component Analysis
Shenglan Liu, Yang Yu
As a widely used method in machine learning, principal component analysis (PCA) shows excellent properties for dimensionality reduction. It is a serious problem that PCA is sensiti…
Local Neighbor Propagation Embedding
Shenglan Liu, Yang Yu
Manifold Learning occupies a vital role in the field of nonlinear dimensionality reduction and its ideas also serve for other relevant methods. Graph-based methods such as Graph Co…
Hierarchic Neighbors Embedding
Shenglan Liu, Yang Yu, Yang Liu +3
Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution,…
Rough extreme learning machine: a new classification method based on uncertainty measure
Lin Feng, Shuliang Xu, Feilong Wang +1
Extreme learning machine (ELM) is a new single hidden layer feedback neural network. The weights of the input layer and the biases of neurons in hidden layer are randomly generated…