TASK DEFINITION: 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].
PROBLEM: ResNet and other architectures that use shortcuts have shown empirical success in several domains and therefore, studying the optimization for such architectures is very valuable. This paper is an attempt to address some of the properties of networks that use shortcuts. Some of the experiments in the paper are interesting. However, there are two main issues with the current paper: 1- linear vs non-linear: I think studying linear networks is valuable but we should be careful not to extend the results to networks with non-linear activations without enough evidence. This is especially true for Hessian as the Hessian of non-linear networks have very large condition number (see the ICLR submission "Singularity of Hessian in Deep Learning") even in cases where the optimization is not challenging. Therefore, I don't agree with the claims in the paper on non-linear networks. Moreover, one plot on MNIST is not enough to claim that non-linear networks behave similar to linear networks. 2- Hessian at zero initial point: The explanation of why we should be interested in Hessain at zero initial point is not acceptable. The zero initial point is not interesting because it is a very particular point that cannot tell us about the Hessian during optimization.

SOLUTION: en

PROBLEM: Observacion de fondo: No se presenta un ejemplo de implementacion (un ejemplo que sea interesante) de una maquina secuencial mediante la metodolgia propuesta y la tradicional cableada con el fin de establecer comparativos y metricas de desempeno. Observaciones de forma: realizar las siguientes correcciones: Omitir el punto final del titulo en espanol. En pagina 3, segunda columna: "... entrada y las variables de estado de la maquina a secuencial." En pagina 4, primera columna: justificacion a la izquierda. En pagina 5, primera columna: "... cantidad de puertos de entrada y salid ..." En pagina 5, primera columna: "... completo a partir de la direccion de cada de cada ...", "... maquina con hasta 15 considerando la suma de ...". En pagina 5, segunda columna: "... maquina con hasta 15 considerando la suma de ...".

SOLUTION: es

PROBLEM: This paper applies RFN for biclustering to overcome the drawbacks in FABIA. The proposed method performs best among 14 biclustering methods, However, my first concern is that from the methodological point of view, the novelty of the proposed method seems small. The authors replied to the same question which another reviewer gave, but the replies were not so convincing. This paper was actually difficult for me to follow. For instance, in Figure 1, a bicluster matrix is constructed as an outer product of $h$ and $w$. $h$ is a hidden unit, but what is $w$? I could not find any definition. Furthermore, I could not know how $h$ is estimated in this method. Therefore, I do NOT understand how this method performs biclustering. Totally, I am not sure that this paper is suitable for publication. Prons: Empirical performance is good. Cons: Novelty of the proposed method Some description in the paper is unclear.

SOLUTION:
en