Patent ID: 9129228
Filing Date: 2015-09-08
Classification: G06N

Abstract:
1. A method for training a target model on a set of training data by performing a plurality of optimization rounds, the method comprising, for each of the plurality of optimization rounds: selecting a set of optimization parameters for the optimization round including a sample size and a damping factor; sampling the training data based on the selected sample size; performing, by one or more processors, the optimization round including optimizing an objective function for the sampled training data; updating a set of target parameters of the target model based on results of the optimization round and the damping factor; and determining, by the one or more processors and using a performance model associated with a set of performance parameters, an optimal sample size for a next optimization round in the plurality of optimization rounds, wherein the performance model is configured to forecast an expected performance of the next optimization round for a given sample size and damping factor based on results of the optimization round, the selected sample size and the damping factor.