instruction:
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].
question:
This work address the problem of supervised learning from strongly labeled data with label noise. This is a very practical and relevant problem in applied machine learning.  The authors note that using sampling approaches such as EM isn't effective, too slow and cannot be integrated into end-to-end training. Thus, they propose to simulate the effects of EM by a noisy adaptation layer, effectively a softmax, that is added to the architecture during training, and is omitted at inference time. The proposed algorithm is evaluated on MNIST and shows improvements over existing approaches that deal with noisy labeled data.  A few comments. 1. There is no discussion in the work about the increased complexity of training for the model with two softmaxes.   2. What is the rationale for having consecutive (serialized) softmaxes, instead of having a compound objective with two losses, or a network with parallel losses and two sets of gradients?  3. The proposed architecture with only two hidden layers isn't not representative of larger and deeper models that are practically used, and it is not clear that shown results will scale to bigger networks.   4. Why is the approach only evaluated on MNIST, a dataset that is unrealistically simple.
answer:
en


question:
In the § Related work: "deeplearning4j 2 provides distributed computing of deep learning framework that runs on the distributed computing Hadoop. However, Hadoop must be installed in all computing nodes, thereby imposing high deployment and maintenance costs."  This is inexact, Deeplearning4j's most basic mode of operation is on a single machine, with Java installed. A GPU is used if available but is not a requirement (Deeplearning4j documentation: 
answer:
en


question:
Observación de fondo:  No se presenta un ejemplo de implementación (un ejemplo que sea interesante) de una máquina secuencial mediante la metodolgía propuesta y la tradicional cableada con el fin de establecer comparativos y métricas de desempeño.  Observaciones de forma: realizar las siguientes correcciones:  Omitir el punto final del título en español.  En página 3, segunda columna: "... entrada y las variables de estado de la máquina a secuencial."  En página 4, primera columna: justificación a la izquierda.  En página 5, primera columna: "... cantidad de puertos de entrada y salid ..."  En página 5, primera columna: "... completo a partir de la dirección de cada de cada ...", "... máquina con hasta 15 considerando la suma de ...".  En página 5, segunda columna: "... máquina con hasta 15 considerando la suma de ...".
answer:

es