We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
The paper proposes an extension of CFDs [1], referred to as extended Conditional Functional Dependencies (eCFDs). In contrast to CFDs, eCFDs specify patterns of semantically relate...
Cooper, Dyer and Frieze studied the problem of sampling H-colourings (nearly) uniformly at random. Special cases of this problem include sampling colourings and independent sets a...
We settle the 1-pass space complexity of (1 ? )approximating the Lp norm, for real p with 1 p 2, of a length-n vector updated in a length-m stream with updates to its coordinate...