vajraadhvan
vajraadhvan OP t1_isvhcdf wrote
Reply to comment by howtorewriteaname in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
I know, right? The responses have been great so far.
vajraadhvan OP t1_iss3bb6 wrote
Reply to comment by hostilereplicator in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
Approximation theory traditionally looks at the structure of function spaces under addition; but approximation spaces under composition are underexamined. Studying approximation spaces under composition may quantitatively explain the outperformance of neural networks, reveal links to dynamical systems, and suggest related architectures.
(Edit: Following the work of Weinan E, Chao Ma, Lei Wu, Ronald DeVore, Gitta Kutyniok, et al.)
vajraadhvan OP t1_isrt93b wrote
Reply to comment by andreichiffa in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
Heartening to hear that a wide range of options are open to me. Thanks a bunch!
vajraadhvan OP t1_isrhwp2 wrote
Reply to comment by xwrxwrxwr in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
This is great! Thanks :)
vajraadhvan OP t1_isrdpvl wrote
Reply to comment by TheDeviousPanda in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
Ah, that's a bit of a shame. I recall seeing a talk called "Towards a Mathematical Theory of Machine Learning" by Weinan E at ICML 2022 (whom I'm citing!), but I'm guessing that's not indicative of the conference as a whole.
Submitted by vajraadhvan t3_y6v03k in MachineLearning
vajraadhvan OP t1_iswelgr wrote
Reply to comment by ZombieRickyB in [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan
Ah, it's by SIAM! Definitely of interest to me, I'll be sure to check the proceedings out.