I met with Professor Verma on May 30 to discuss my initial approach for developing a metric learning algorithm that retains the structure of the clustered data. After presenting several ideas involving Mahalanobis distance and other linear transformations, it was clear that I was too focused on solving for the metric learning portion of the problem and neglected to address how I could incorporate structural integrity into the loss function. Professor Verma suggested that I read about Bayesian nonparametrics to get some ideas.