Showing stat.MLShow all
3 papers · 1 filter
stat.ML2021
Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning
Hankui Peng, Nicos G. Pavlidis
Spectral-based subspace clustering methods have proved successful in many challenging applications such as gene sequencing, image recognition, and motion segmentation. In this work…
stat.ML2019
Subspace Clustering with Active Learning
Hankui Peng, Nicos G. Pavlidis
Subspace clustering is a growing field of unsupervised learning that has gained much popularity in the computer vision community. Applications can be found in areas such as motion…
stat.ML2019
Subspace Clustering of Very Sparse High-Dimensional Data
Hankui Peng, Nicos Pavlidis, Idris Eckley +1
In this paper we consider the problem of clustering collections of very short texts using subspace clustering. This problem arises in many applications such as product categorisati…