3 citations · 8 across the 7 of their papers we have counts for
7 papers
A Provable Splitting Approach for Symmetric Nonnegative Matrix Factorization
Xiao Li, Zhihui Zhu, Qiuwei Li +1
The symmetric Nonnegative Matrix Factorization (NMF), a special but important class of the general NMF, has found numerous applications in data analysis such as various clustering…
Rethinking Symmetric Matrix Factorization: A More General and Better Clustering Perspective
Mengyuan Zhang, Kai Liu
Nonnegative matrix factorization (NMF) is widely used for clustering with strong interpretability. Among general NMF problems, symmetric NMF is a special one that plays an importan…
Spherical Matrix Factorization
Kai Liu
Matrix Factorization plays an important role in machine learning such as Non-negative Matrix Factorization, Principal Component Analysis, Dictionary Learning, etc. However, most of…
Robust Principal Component Analysis: A Construction Error Minimization Perspective
Kai Liu, Yarui Cao
In this paper we propose a novel optimization framework to systematically solve robust PCA problem with rigorous theoretical guarantee, based on which we investigate very computati…
Exact Sparse Orthogonal Dictionary Learning
Kai Liu, Yongjian Zhao, Hua Wang
Over the past decade, learning a dictionary from input images for sparse modeling has been one of the topics which receive most research attention in image processing and compresse…
RRCN: A Reinforced Random Convolutional Network based Reciprocal Recommendation Approach for Online Dating
Linhao Luo, Liqi Yang, Ju Xin +6
Recently, the reciprocal recommendation, especially for online dating applications, has attracted more and more research attention. Different from conventional recommendation probl…
Wasserstein Autoencoders for Collaborative Filtering
Jingbin Zhong, Xiaofeng Zhang
The recommender systems have long been investigated in the literature. Recently, users' implicit feedback like `click' or `browse' are considered to be able to enhance the recommen…