This online summer school aims to introduce the progress of deep learning theory in last several years, including mean field theory, neural tangent kernel, function space theory, implicit regularization, frequency principle etc. These interactions among different viewpoints may shed light on the development of deep learning theory.
Audience: Senior undergraduates, graduates, and young researchers.
July 16~July 22，2020
Detailed Zoom Info could be found in the Schedule.
Please register online.
Preference is given to, but not limited to, applicants with a basic understanding of ordinary differential equations and probability. No registration fee.
|Jul 16, 2020||09:30-12:00||Accuracy and trainability of neural networks: a mean-field perspective on approximation and optimization||Grant M. Rotskoff||962-308-15257|
|Jul 16, 2020||15:00-17:30||Neural tangent kernel: convergence and generalization in neural networks||Arthur Jacot||681-823-42064|
|Jul 17, 2020||09:30-12:00||A function space theory and generalization error estimates for neural network models||Chao Ma||912-899-29245|
|Jul 18, 2020||09:30-12:00||Towards understanding the implicit regularization in deep learning||Lei Wu||645-275-76523|
|Jul 19, 2020||09:30-12:00||Frequency principle: linear model and general theory||Luo Tao, Yaoyu Zhang||999-355-46463|
|Jul 22, 2020||09:30-12:00||Neural tangent kernel made practical||Wei Hu||969-766-38784|
Zoom Password: 738669
If the above Zoom IDs does not work, we would shift to a backup Zoom ID: 266-664-3379 with the same password.