Hi Everyone,
Tomorrow Jacob will be giving us group meeting. Please see below for the
title and abstract of his talk.
Jennifer
-----------------------------------
Title: Uncovering and Exploiting Sparsity in Neural Networks
Abstract: Neural networks exhibit various kinds of sparsity. The most
obvious type of sparsity is the structural connectivity of the network:
relatively few neurons are synaptically linked to each other. I will begin
by reviewing an experimental proposal to recover the sparse connectivity
matrix by randomly expressing green fluorescent protein in various neurons
and then applying compressed sensing to recover the connectivity. Moving
beyond structural sparsity, I will discuss the idea of "functional
sparsity"--the idea that while a neural network is governed by a vast
number of microscopic parameters, only a few combinations of these
parameters might be relevant to the macroscopic behavior of the network.
In particular, I will propose that the recent idea of parameter space
compression could be applied to neurons to find a minimal set of
macroscopic characteristics required to describe a neural network, and
illustrate how it might work within the context of a model for learning and
memory known as spike-time-dependent plasticity.
_______________________________________________
Aspuru-meetings-list mailing list
Aspuru-meetings-list(a)lists.fas.harvard.edu
https://lists.fas.harvard.edu/mailman/listinfo/aspuru-meetings-list