In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].

This paper introduces a hierarchical clustering method using learned CNN features to build 'the tree of life'. The assumption is that the feature similarity indicates the distance in the tree. The authors tried three different ways to construct the tree: 1) approximation central point 2) minimum spanning tree and 3) multidimensional scaling based method. Out of them, MDS works the best. It is a nice application of using deep features. However, I lean toward rejecting the paper because the following reasons:  1) All experiments are conducted in very small scale. The experiments include 6 fish species, 11 canine species, 8 vehicle classes. There are no quantitative results, only by visualizing the generated tree versus the wordNet tree. Moreover, the assumption of using wordNet is not quite valid. WordNet is not designed for biology purpose and it might not reflect the true evolutionary relationship between species.  2) Limited technical novelty. Most parts of the pipeline are standard, e.g. use pretrained model for feature extraction, use previous methods to construct hierarchical clustering. I think the technical contribution of this paper is very limited.
en

This paper considers the problem of model-based policy search. The authors  consider the use of Bayesian Neural Networks to learn a model of the environment and advocate for the $\alpha$-divergence minimization rather than the more usual  variational Bayes.   The ability of alpha-divergence to capture bi-modality however  comes at a price and most of the paper is devoted to finding tractable approximations.  The authors therefore use the approach of Hernandez-Lobato et al. (2016) as proxy to the alpha-divergence .   The environment/system dynamics is clearly defined as a well as the policy parametrization  (section 3) and would constitute a useful reference point for other researchers.  Simulated roll-outs, using the learned model, then provide samples of the expected  return. Since a model of the environment is available, stochastic gradient descent  can be performed in the usual way, without policy gradient estimators, via automatic  differentiation tools.   The experiments demonstrate that alpha-divergence is capable of capturing multi-model  structure which competing methods (variational Bayes and GP) would otherwise struggle with. The proposed approach also compares favorably in a real-world batch setting.  The paper is well-written, technically rich and combines many recent tools  into a coherent algorithm. However, the repeated use of approximations to original  quantities seems to somehow defeat the benefits of the original problem formulation.  The scalability and computational effectiveness of this approach is also questionable  and I am uncertain if many problem would warrant such complexity in their solution.  As with other Bayesian methods, the proposed approach would probably shine in low-samples  regime and in this case might be preferable to other methods in the same class (VB, GP).
en

Este es un trabajo que muestra la experiencia de incorporación de un robot para realizar soldaduras en una empresa de Antofagasta.  La incorporación de tecnología es importante en la Empresa y me parece importante que las empresas confíen en las Universidades para hacerlo. Es un tema importante de revisar en las jornadas.  Revisar aspectos de formato (redacción en tercera persona, ortografía, algunas imágenes no son claras, contiene 7 páginas y sólo eran consideradas 6 o 10) No queda clara si la Empresa utiliza robot y soldadores o sólo robots. No hay una evaluación de los beneficios en cuanto a dinero percibidos por la utilización del robot.

es