Randomized Optimum models (RandOMs) are probabilistic models that de- fine distributions over structured outputs by making use of structured opti- mization procedures within the model definition. This chapter reviews Ran- dOMs and develops a new application of RandOMs to the problem of factorizing shortest paths; that is, given observations of paths that users take to get from one node to another on a graph, learn edge-specific and user- specific trait vectors such that inner products of the two define user-specific edge costs, and the distribution of observed paths can be explained as users taking shortest paths according to noisy samples from their cost function.
@inbook{tarlow2016factorizing, year = {2016}, author = {Tarlow, Daniel and Gaunt, Alexander and Adams, Ryan P. and Zemel, Richard S.}, title = {Factorizing Shortest Paths with Randomized Optimum Models}, booktitle = {Perturbations, Optimization, and Statistics}, publisher = {MIT Press}, address = {Cambridge, MA}, keywords = {structured prediction} }