A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
A novel center-based clustering algorithm is proposed in this paper. We first formulate clustering as an NP-hard linear integer program and we then use linear programming and the ...
In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...