Document representation and indexing is a key problem for document analysis and processing, such as clustering, classification and retrieval. Conventionally, Latent Semantic Index...
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He, Wei Vivian Zhang, Jiawei Han
We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsu...
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
In this work we construct scale invariant descriptors (SIDs) without requiring the estimation of image scale; we thereby avoid scale selection which is often unreliable. Our start...