I took a seminar course on deep learning in the spring quarter, instructed by Prof. Fei Sha. I think the reading list in the syllabus is quite good and helpful, so I decide to blog about it.
As part of course requirement, I wrote three 5-page summaries of the corresponding topic (depth, regularization, optimization) in deep learning, which roughly follow the papers listed in the course syllabus. Hope you find them useful. Should be a quick and easy read ;)
Current Topics in Artificial Intelligence: Depth
Current Topics in Artificial Intelligence: Regularization
Current Topics in Artificial Intelligence: Optimization