This paper discusses the topic of dimensionality reduction for k-means clustering. We prove that any set of n points in d dimensions (rows in a matrix A ∈ Rn×d ) can be project...
We propose the use of random projections with a sparse matrix to maintain a sketch of a collection of high-dimensional data-streams that are updated asynchronously. This sketch al...
Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Ch...
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...
Abstract. Dialectometry produces aggregate distance matrices in which a distance is specified for each pair of sites. By projecting groups obtained by clustering onto geography on...
John Nerbonne, Peter Kleiweg, Wilbert Heeringa, Fr...
In this paper, we propose a new method based on wavelet transform, statistical features and central moments for both graphics and scene text detection in video images. The method ...
Palaiahnakote Shivakumara, Trung Quy Phan, Chew Li...