Computational Learning Theory and Fourier Analysis
Organizers:
Alexandros Eskenazis and Paata Ivanisvili
ONLINE
October 10- October 14, 2022
Computational Learning Theory and Fourier Analysis
Organizers:
Alexandros Eskenazis and Paata Ivanisvili
ONLINE
October 10- October 14, 2022
This year the summer/fall school will take place online due to pandemic.
The total number of participants is limited to 15 (including 2 organizers).
Participants can be graduate students or postdocs who will be interested in learning new challenging problems in Learning Theory. Undergraduate students are also welcome to apply.
Each participant will choose a paper from the list and prepare two talks (each 50 minutes long). The first talk will be more introductory containing the basic definitions and the summary of the results, and the second talk will be more about the details of the proofs.
Participants will need to submit 4-6 page summary of the talk by September 25th, 2022 for proceedings. Here is a sample of the summary written for this paper.
The summer/fall school is funded by the NSF. Ideally we would arrange a meeting in a resort, however, due to pandemic we decided to make an exception this year and organize the summer/fall school online. Nonlocal (not UCI affiliated) participants based in US and having SSN will receive a stipend (funded by NSF CAREER DMS-2152401). If you are interested to participate
please submit your application
as soon as possible but no later than July 3rd, 2022. Please let us know your status (grad student, postdoc, etc), your research area, and very briefly why are you interested to participate in this summer/fall school. The accepted participants will receive a confirmation email in the second week of July, 2022 together with further instructions.
Inspired by the Summer School in Analysis.