Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
The class of low-density parity-check (LDPC) codes is attractive, since such codes can be decoded using practical message-passing algorithms, and their performance is known to app...
In this paper we articulate a new modeling paradigm for both local and global editing on complicated point set surfaces of arbitrary topology. In essence, the proposed technique l...
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
Abstract. We present a compiler for definitions made by pattern matching on inductive families in the Coq system. It allows to write structured, recursive dependently-typed functi...