Suppose thatM is an in nite structure with nite relational vocabulary such that every relation symbol has arity at most 2. IfM is simple and homogeneous then its complete theory is supersimple with nite SU-rank which cannot exceed the number of complete 2-types over the empty set.

This paper presents our work on the 2016 CLEF eHealth Task 3.We used Indri to conduct our experiments. We used CHV to expand query and proposed a learning-to-rank algorithm to re-rank the result.

Symmetrizations of tensors by irreducible characters of the symmetric group serve as natural analogues of symmetric and skew-symmetric tensors. The question of when a symmetrized decomposable tensor is non-zero is intimately related to the rank partition of a matroid extracted from the tensor. In this paper we characterize the non-vanishing of the symmetrization of certain partially symmetrized...

We note here, in answer to a question of Poizat, that the Morley and Lascar ranks need not coincide in differentially closed fields. We will approach this through the (perhaps) more fundamental issue of the variation of Morley rank in families. We will be interested here only in sets of finite Morley rank. § 1 consists of some general lemmas relating the above issues. § 2 points out a family of...

The pivoted QLP decomposition is computed through two consecutive QR decompositions. It an approximation to the computationally prohibitive singular value (SVD). This work concerned with a partial of matrices exploitation random sampling. method presented tailored for low-rank and called Random...

Rank minimization is of interest in machine learning applications such as recommender systems and robust principal component analysis. Minimizing the convex relaxation to rank problem, nuclear norm, an effective technique solve problem with strong performance guarantees. However, nonconvex relaxations have less estimation bias than norm can more accurately reduce effect noise on measurements. W...