This repository contains the PyTorch implementation for MVASM. TKDE 2020

Datasets

• COIL20
• MNIST
• YALE

Three heterogeneous feature descriptors are ISO.m, LDA.m, and NPE.m.

Parameters

For different datasets, their parameters can be set as follows:

• COIL: qStart = 1; qNum = 96; qStride = 0.01; rStart = 0; rNum = 4; rStride = 0.1
• MNIST: qStart = 1.6; qNum = 2; qStride = 0.01; rStart = 0; rNum = 2; rStride = 0.1
• YALE: qStart = 1; qNum = 11; qStride = 0.01; rStart = 0; rNum = 9; rStride = 0.1

Reference

• Multi-View K-Means Clustering on Big Data. (IJCAI,2013).
• Discriminatively Embedded K-Means for Multi-view Clustering. (CVPR,2016)
• Robust and Sparse Fuzzy K-Means Clustering. (IJCAI2016)
• A new simplex sparse learning model to measure data similarity for clustering (AAAI2015)
• COMPACT: A Comparative Package for Clustering Assessment. (ISPA2005)
• https://github.com/ZJULearning/MatlabFunc/tree/master/Clustering