Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
Pengcheng Wu, Steven C. H. Hoi, Duc Dung Nguyen, Y...
We present a new stochastic model for complex networks, based on a spatial embedding of the nodes, called the Spatial Preferred Attachment (SPA) model. In the SPA model, nodes have...
William Aiello, Anthony Bonato, C. Cooper, Jeannet...
We present a novel variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher dimensional space of distance transforms. In...
Xiaolei Huang, Nikos Paragios, Dimitris N. Metaxas