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I have some basic knowledge about deep learning methods (fully connected and convolutional NNs). I would like to expand my knowledge of deep learning which could be beneficial for an operations researcher. What resource/book would you suggest for reading?

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This is the book that I used for my class at VT: https://www.deeplearningbook.org/

This is another book that was recommended there: https://d2l.ai/

This book on online learning is also useful: https://www.cs.huji.ac.il/~shais/papers/OLsurvey.pdf "Online Learning and Online Convex Optimization" by Shai Shalev-Shwartz.

Some papers I found helpful from Van Hentenryck: "Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method", "Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods".

Also, this paper is helpful: https://arxiv.org/pdf/1705.03341.pdf "Stable Architectures for Deep Neural Networks"

If you have a graph background: https://web.njit.edu/~ym329/dlg_book/

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  • $\begingroup$ Thanks for sharing this. The 4th mentioned references are very interesting. $\endgroup$
    – A.Omidi
    Jul 14, 2023 at 10:32

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