57 citations · 159 across the 36 of their papers we have counts for
4 papers · 1 filter
Kernel k-Means, By All Means: Algorithms and Strong Consistency
Debolina Paul, Saptarshi Chakraborty, Swagatam Das +1
Kernel -means clustering is a powerful tool for unsupervised learning of non-linearly separable data. Since the earliest attempts, researchers have noted that such algorithms of…
Biconvex Clustering
Saptarshi Chakraborty, Jason Xu
Convex clustering has recently garnered increasing interest due to its attractive theoretical and computational properties, but its merits become limited in the face of high-dimens…
Simple and Scalable Sparse k-means Clustering via Feature Ranking
Zhiyue Zhang, Kenneth Lange, Jason Xu
Clustering, a fundamental activity in unsupervised learning, is notoriously difficult when the feature space is high-dimensional. Fortunately, in many realistic scenarios, only a h…
Entropy Regularized Power k-Means Clustering
Saptarshi Chakraborty, Debolina Paul, Swagatam Das +1
Despite its well-known shortcomings, -means remains one of the most widely used approaches to data clustering. Current research continues to tackle its flaws while attempting to…