Recommended papers for deep learning based classification? I'm working on a project where I have to build a classifier using Deep Neural Networks and I will be dealing with big data. I am familiar with neural networks, yet not an expert. I can obviously find a huge amount of literature online regarding deep learning but mostly will be convnets related.
Are there any good research papers for DNN-based classifiers or should I just stack more layers? I want to get some insight about the architecture and training process. 
P.S: Using Deep Neural Networks is mandatory even if the accuracy is low, but it would be great if it worked out.
Maybe reading papers is a bit hard, because they usually don't explain everything. I suggest you watching deep learning specialization by professor Andrew Ng, which is brief and easy to figure out. If you insist on reading papers, this three sequential articles may help you. Choosing neural networks highly depend on your task. For most computer vision tasks convolutional neural nets are used. You can also take a look at here which contains different resources and discussions and many other useful stuff.