206 citations · 210 across the 4 of their papers we have counts for
4 papers
Multiple Sample Clustering
Xiang Wang, Tie Liu
The clustering algorithms that view each object data as a single sample drawn from a certain distribution, Gaussian distribution, for example, has been a hot topic for decades. Man…
Uncovering Group Level Insights with Accordant Clustering
Amit Dhurandhar, Margareta Ackerman, Xiang Wang
Clustering is a widely-used data mining tool, which aims to discover partitions of similar items in data. We introduce a new clustering paradigm, \emph{accordant clustering}, which…
A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning
Buyue Qian, Xiang Wang, Ian Davidson
A significant challenge to make learning techniques more suitable for general purpose use is to move beyond i) complete supervision, ii) low dimensional data, iii) a single task an…
On Constrained Spectral Clustering and Its Applications
Xiang Wang, Buyue Qian, Ian Davidson
Constrained clustering has been well-studied for algorithms such as -means and hierarchical clustering. However, how to satisfy many constraints in these algorithmic settings ha…