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CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account...
Background: Genome-wide association studies (GWAS) prove to be a powerful approach to identify the genetic basis of various human diseases. Here we take advantage of existing GWAS data and attempt to build a framework to understand the complex relationships among diseases. Specifically, we examined 49 diseases from all available GWAS with a cascade approach by exploiting network analysis to study...
In this paper, we study the problem of large scale image retrieval by developing a new class of bag-of-features to encode geometric information of objects within an image. Beyond existing orderless bag-of-features, local features of an image are first projected to different directions or points to generate a series of ordered bag-of-features, based on which different families of spatial bag-of-features...
How to capture biologically important conformational transitions from structures have been of key interest in computational biology. It is generally recognized that normal modes derived from structure-based potentials can well represent functional movements in lots of biomolecules. Recently normal mode analysis was successfully used in an iterative manner to explore protein conformational transition...
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