Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Abstract. The paper considers the problem of semi-supervised multiview classification, where each view corresponds to a Reproducing Kernel Hilbert Space. An algorithm based on co-...
Abstract. We consider a problem that is related to the “Universal Encoding Problem” from information theory. The basic goal is to find rules that map “partial information”...
Abstract. Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way f...
Abstract: Our main contribution is to propose a novel model selection methodology, expectation minimization of information criterion (EMIC). EMIC makes a significant impact on the...