We present a way to add user's background knowledge to formal concept analysis. The type of background knowledge we deal with relates to relative importance of attributes in ...
This paper aims to introduce the robustness against noise into the spectral clustering algorithm. First, we propose a warping model to map the data into a new space on the basis o...
Traditional clustering algorithms work on "flat" data, making the assumption that the data instances can only be represented by a set of homogeneous and uniform features...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
We present a method to improve the performance of face retrieval in news videos by using the relevant-set correlation (RSC) clustering model. In this method, faces of a person are...
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...