1. A computer-implemented method comprising: receiving, at a computing device including one or more processors, a plurality of photos; selecting, at the computing device, a subset of the plurality of photos by performing joint global maximization of photo quality and photo diversity using a quality metric for each of the plurality of photos and a similarity matrix for the plurality of photos, the quality metric for a specific photo being indicative of a quality of the specific photo, the similarity matrix being indicative of a similarity between each unique pair of photos of the plurality of photos, wherein the quality metric and the similarity matrix are each determined based an analysis of a reference photo collection that includes a plurality of reference photos, a quality weight for each reference photo, and a similarity weight for each unique pair of reference photos; determining, at the computing device, a plurality of clusters for the subset of the plurality of photos using a hierarchical clustering algorithm, the plurality of clusters including less than all of the subset of the plurality of photos, each of the plurality of clusters including one or more distinct photos from the subset of the plurality of photos; storing, at the computing device, the subset of the plurality of photos arranged based on the plurality of clusters; receiving, at the computing device, user input with respect to the subset of the plurality of photos arranged based on the one or more clusters, the user input corresponding to at least one of adding a first specific photo from a remainder of the plurality of photos to a specific cluster, deleting a second specific photo from the specific cluster, and moving the second specific photo from the specific cluster to another one of the plurality of clusters; adjusting, at the computing device, at least one of: (i) the quality metrics and (ii) the similarity matrix when the user input corresponds to at least one of adding the first specific photo from the remainder of the plurality of photos to the specific cluster and deleting the second specific photo from the specific cluster to obtain at least one of modified quality metrics and a modified similarity matrix, (iii) the subset of the plurality of photos when the user input corresponds to at least one of adding the first specific photo from the remainder of the plurality of photos to the specific cluster and deleting the second specific photo from the specific cluster to obtain a first modified subset of the plurality of photos, and (iv) the plurality of clusters when the user input corresponds to moving the second specific photo from the specific cluster to another one of the plurality of clusters to obtain a first plurality of modified clusters; and when at least one of the quality metrics and the similarity matrix is adjusted: selecting, at the computing device, a second modified subset of the plurality of photos by performing joint global maximization of photo quality and photo diversity using at least one of the modified quality metrics and the modified similarity matrix, determining, at the computing device, a second plurality of modified clusters for the second modified subset of the plurality of photos using the hierarchical clustering algorithm, each of the second plurality of modified clusters including one or more distinct photos from the second modified subset of the plurality of photos, and storing, at the computing device, the second modified subset of the plurality of photos arranged based on the second plurality of modified clusters.