After reviewing papers on Gaussian Process and gradient descent without a gradient (Flaxman, 2008), I met with Professor Verma on 6/15 and we discussed the methodologies and applicability to our problem at hand. While Gaussian Process may not be the relevant tool for clustering, its underlying theory is helpful to my understanding in regression and classification. Professor Verma assigned a problem from his ML class last fall to help me solidify my knowledge in Gaussian Process.

As for the methodology from the Flaxman paper, I drafted an algorithm that computes the structural integrity of the clusters by comparing the effective cluster sizes determined by EM/GMM to the true labels of the data, and using the approximated gradient to minimize the loss function. I will try to implement the algorithm in the coming week.