29 дек. 2023 г. · Unless it is one of the big national laboratories at Google, Microsoft, etc. Is theoretical machine learning used anywhere else?

10 февр. 2024 г. · Which topics should I master before taking a deep dive into it? Are there beginner papers that one could read to have a general idea about how ...

28 дек. 2023 г. · In general I feel like anything theoretical moves slower than the applied side. Then again, I'm not well-versed with theoretical ML so take it with a grain of ...

17 нояб. 2024 г. · In case your brain starts to melt from all the math, Understanding Deep Learning by Prince is a pretty solid minimal-math overview of ML theory.

22 авг. 2024 г. · I was wondering if there are some interesting ways to combine machine learning and theoretical computer science.

11 авг. 2022 г. · I would suggest you to ask for guidance on a statistics department, where people will review your paper under the probability theory perspective.

19 мая 2023 г. · This book develops an effective theory approach to understanding deep neural networks of practical relevance.

22 апр. 2021 г. · Knowledge of "basic" mathematics required to even talk about machine learning (e.g. probability theory, algebra 101, calculus 101).

11 мая 2024 г. · I am looking for subjects that dive deep into the theoretical underpinnings, probabilistic models, optimization techniques, and mathematical ...

9 апр. 2024 г. · I heard from couple of sources that Practical Deep Learning has been developing way faster than theoretical ML, so many questions remain unanswered.