Learning Convex Optimization Models

A convex optimization model predicts an output from input by solving a problem. The class of models is large, and includes as special cases many well-known like linear logistic regression. We propose heuristic for learning the parameters in given dataset input-output pairs, using recently developed methods differentiating solution problem with respect to its parameters. describe three general classes models, maximum posteriori (MAP) utility maximization agent present numerical experiment each.