142 citations · 372 across the 22 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
cs.CV2016★ 2 cited
A Fast Factorization-based Approach to Robust PCA
Chong Peng, Zhao Kang, Qiang Chen
Robust principal component analysis (RPCA) has been widely used for recovering low-rank matrices in many data mining and machine learning problems. It separates a data matrix into…
cs.IR2016★ 19 cited
Top-N Recommendation on Graphs
Zhao Kang, Chong Peng, Ming Yang +1
Recommender systems play an increasingly important role in online applications to help users find what they need or prefer. Collaborative filtering algorithms that generate predict…
cs.IR2016★ 21 cited
Top-N Recommender System via Matrix Completion
Zhao Kang, Chong Peng, Qiang Cheng
Top-N recommender systems have been investigated widely both in industry and academia. However, the recommendation quality is far from satisfactory. In this paper, we propose a sim…