We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...
We develop an approach to intrinsic dimension estimation based on k-nearest neighbor (kNN) distances. The dimension estimator is derived using a general theory on functionals of k...
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...
This paper presents an hybrid adaptive system for induction of forest of trees from data streams. The Ultra Fast Forest Tree system (UFFT) is an incremental algorithm, with consta...