Abstract. A new dictionary learning method for exact sparse representation is presented in this paper. As the dictionary learning methods often iteratively update the sparse coeffi...
We introduce a new technique for proving kernelization lower bounds, called cross-composition. A classical problem L cross-composes into a parameterized problem Q if an instance o...
Hans L. Bodlaender, Bart M. P. Jansen, Stefan Krat...
: The explosion of highthroughput interaction data from proteomics studies gives us the opportunity to integrate Protein-Protein Interactions (PPI) from different type of interacti...
Powell Patrick Cheng Tan, Daryanaz Dargahi, Freder...
Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
We introduce locally-rigid motion, a general framework for solving the M-point, N-view structure-from-motion problem for unknown bodies deforming under orthography. The key idea i...