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Sure, but if I'm reading a paper that starts to show equations, I can start getting lost. There's no "knowning" their garbage because it gets over-math'd. I get

Sure, but if I'm reading a paper that starts to show equations, I can start getting lost. There's no "knowning" their garbage because it gets over-math'd. I get that's a sign of a bad paper, but my only argument for "why" is because I can't understand it. Not exactly the strongest defense. The same for stats - if you are uncomfortable with them, then seeing terms like Wilcoxon and Spearman are just confusing. Should the number be high? Low? Or simply, why do some papers have one and others have the other? If you are shaky on stats, its easier to just accept a particular formula was used even if it is not appropriate.

codesushi42 7y ago
My point was you can understand a paper without understanding all of the proofs shown. Following the proof isn't essential to understanding what the technique is. There are papers with bad proofs but valid techniques. Because NNs techniques are difficult if not impossible to prove mathematically. Empirical data is much more valuable.
- tsumnia 7y ago
  Right, but my point is what if I want to implement the math? Without deep diving into my research, I disagree with your second sentence entirely. It is why I think we are also seeing the rise in Jupyter notebook still articles - because you can explicitly follow along. As a rule of thumb, I try to assume no one understands anything and so I must be very explicit in anything I teach. I find this to be a better baseline than assuming everyone already knows what I'm about to teach. Back to my point - if I want to implement something I've read in a journal article on something like queuing theory that I'd like to work into my CS education research, having a weaker foundation on math has made it harder for me to implement someone's work.
  - codesushi42 7y ago
    What you said is true, lacking the mathematical intuition will limit you. But understanding the proof is not essential to implementing the approach.

codesushi42 7y ago

My point was you can understand a paper without understanding all of the proofs shown. Following the proof isn't essential to understanding what the technique is. There are papers with bad proofs but valid techniques. Because NNs techniques are difficult if not impossible to prove mathematically. Empirical data is much more valuable.

tsumnia 7y ago
Right, but my point is what if I want to implement the math? Without deep diving into my research, I disagree with your second sentence entirely. It is why I think we are also seeing the rise in Jupyter notebook still articles - because you can explicitly follow along. As a rule of thumb, I try to assume no one understands anything and so I must be very explicit in anything I teach. I find this to be a better baseline than assuming everyone already knows what I'm about to teach. Back to my point - if I want to implement something I've read in a journal article on something like queuing theory that I'd like to work into my CS education research, having a weaker foundation on math has made it harder for me to implement someone's work.
- codesushi42 7y ago
  What you said is true, lacking the mathematical intuition will limit you. But understanding the proof is not essential to implementing the approach.