报告题目：Learning with norm-based neural networks: model capacity and computational-statistical gaps

报 告 人：刘方辉 博士

报告人所在单位：University of Warwick, UK

报告日期：2024年9月4日

报告时间：14:30-15:30

报告地点：光华楼东主楼 2001

报告摘要：

In this talk, I will discuss some fundamental questions in modern machine learning:

  -What is the suitable model capacity of over-parameterized models?

  -What is the suitable function space for feature learning?

  -Which function can be learned by two-layer neural networks, statistical and/or computational efficiently?

  -What is the computational-statistical gap behind this?

My talk will partly answer the above questions, both theoretically and empirically.