Abstract:
The perceptron is a toy model of a simple neural network that stores a collection of given patterns. Its analysis reduces to a simple problem in high-dimensional geometry, namely, understanding the intersection of the cube (or sphere) with a collection of random half-spaces. Despite the simplicity of this model, its high-dimensional asymptotics are not well understood. I will describe what is known and present recent results.
This is a joint work with Jian Ding.
Biography:
Nike Sun is a faculty member in the MIT mathematics department.
MIT Statistics and Data Science Center host guest lecturers from around the world in this weekly seminar.