This paper presents the results of EXONA in the Ontology Alignment Evaluation Initiative (OAEI) 2015. EXONA is an automatic instance-based ontology alignment systems in which we parse ontology as rst step. In the second step, we index instances of the rst ontology. These indexed instances will be applied for the querying phase. In the last step, our system aligns instances based by aggregating ...

This paper describes the SINAI team participation in the ImageCLEF campaign. The SINAI research group has participated in both the ad hoc task and the medical task. The experiments accomplished in both cases result from very different approaches. For the ad hoc task the main Information Retrieval (IR) system used combines the document lists retrieved by two IR systems, and uses online translato...

Mixture distributions arise in many parametric and non-parametric settings—for example, in Gaussian mixture models and in non-parametric estimation. It is often necessary to compute the entropy of a mixture, but, in most cases, this quantity has no closed-form expression, making some form of approximation necessary. We propose a family of estimators based on a pairwise distance function between...

We use the lace expansion to study long-distance decay of two-point function weakly self-avoiding walk on integer lattice $$\mathbb {Z}^d$$ in dimensions $$d>4$$ , vicinity critical point, and prove an upper bound $$|x|^{-(d-2)}\exp [-c|x|/\xi ]$$ where correlation length $$\xi $$ has a square root divergence at point. As application, we that for discrete torus $$d{>}4$$ “plateau.” also discuss...

Variational inference (VI) is widely used as an efficient alternative to Markovchain Monte Carlo. It posits a family of approximating distributions q and findsthe closest member to the exact posterior p. Closeness is usually measured via adivergence D(q||p) from q to p. While successful, this approach also has problems.Notably, it typically leads to underestimation of the poster...

This paper studies the complexity of estimating Renyi divergences of a distribution p observed from samples, with respect to a baseline distribution q known a priori. Extending the results of Acharya et al. (SODA’15) on estimating Renyi entropy, we present improved estimation techniques together with upper and lower bounds on the sample complexity. We show that, contrarily to estimating Renyi e...