In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
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,...