Abstract: Described herein are example systems and operations for enhancing response prediction and bidding decision making. A feature recommendation controller may include a factorization machine that generates a set of combinations of contextual and advertiser features yielding high expected response rates. A bidding controller may implement a multi-arm bandit system that uses Thompson sampling to select an optimal one of the feature combinations that corresponds to a highest expected response rate. The bidding controller may compare the corresponding highest expected response rate with a threshold response rate associated with a pacing rate to determine whether to place a bid for a received ad request.

Abstract: A computer system implementing a method for ad realization prediction may be configured to receive a plurality of target realization factors associated with a target ad display opportunity; determine a reference realization probability score of the target ad display opportunity based on a global reference realization probability distribution associated with an ad display realization probability decision tree; using the reference realization probability score, determine an ad realization probability score of the target ad display opportunity according to a piecewise calibrated realization probability function; and return the ad realization probability score.