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Normal_Flan_1269 t1_iti0m49 wrote

Reply to comment by Red-Portal in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan

None of those are useful for creating new statistical learning methods or pushing the boundaries of statistical learning as functional analysis, measure theory, real analysis, and statistics. Like cryptography is useless for developing new regularized regression methods, who gives a shit about complexity theory? Like you guys think ML theory and statistical learning is a CS branch. Like you guys coin the term machine learning and think it’s a branch of CS… very far from the truth. Mathematicians and statisticians have been running circles around you guys doing this for decades. Know your place

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Red-Portal t1_iti0ug1 wrote

Wait what? The core of learning theory is algorithm analysis and complexity theory! Please take any learning theory textbook or course first before making such groundless judgements. God the freakin definition of "PAC learnable" is algorithm-theoric.

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Normal_Flan_1269 t1_iti100x wrote

It’s literally called statistical learning theory

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Red-Portal t1_iti13ms wrote

Yes that's why you need at least "undergraduate" statistics knowledge.

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Normal_Flan_1269 t1_iti2r8e wrote

Lol that’s so false. Undergrad stats is not nearly enough, not even undergrad math. You can get away with just knowing how to code a little bit but it’s way more math and stats. Cs majors are just trained to be software engineers and nothing else. I’m a math and stats major and run circles around them in AI courses because they don’t have any technical depth mathematically.

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