Domain Adaptive Learning Based on Sample-Dependent and Learnable Kernels

no code implementations • 18 Feb 2021 • Xinlong Lu, Zhengming Ma, Yuanping Lin

The second contribution lies on that we apply PDQK to Domain Adaptive Learning (DAL).

BIG-bench Machine Learning

Riemannian Manifold Optimization for Discriminant Subspace Learning

no code implementations • 20 Jan 2021 • Wanguang Yin, Zhengming Ma, Quanying Liu

Linear discriminant analysis (LDA) is a widely used algorithm in machine learning to extract a low-dimensional representation of high-dimensional data, it features to find the orthogonal discriminant projection subspace by using the Fisher discriminant criterion.

General Classification Image Classification +1

HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction

no code implementations • 18 Jan 2021 • Wanguang Yin, Youzhi Qu, Zhengming Ma, Quanying Liu

However, most of tensor decomposition methods are the linear feature extraction techniques, which are unable to reveal the nonlinear structure within high-dimensional data.

Clustering Dimensionality Reduction +3