{"type":"ScholarlyArticle","title":"Training-Time Optimization of a Budgeted Booster","authors":[{"name":"Yi Huang","slug":"yi-huang","given":"Yi","family":"Huang","affiliation":""},{"name":"Brian Powers","slug":"brian-powers","given":"Brian","family":"Powers","affiliation":""},{"name":"Lev Reyzin","slug":"lev-reyzin","given":"Lev","family":"Reyzin","affiliation":""}],"abstract":"We consider the problem of feature-efficient prediction - a setting where features have costs and the learner is limited by a budget constraint on the total cost of the features it can examine in test time. We focus on solving this problem with boosting by optimizing the choice of base learners in the training phase and stopping the boosting process when the learner's budget runs out. We experimentally show that our method improves upon the boosting approach AdaBoostRS [Reyzin, 2011] and in many cases also outperforms the recent algorithm SpeedBoost [Grubb and Bagnell, 2012]. We provide a theoretical justication for our optimization method via the margin bound. We also experimentally show that our method outperforms pruned decision trees, a natural budgeted classifier.","doi":null,"url":"https://ijcai.org/proceedings/2015/504","pdf":"https://ijcai.org/proceedings/2015/0504.pdf","markdown":"https://ijcai.org/proceedings/2015/504.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/504","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Machine Learning","track":"Special Track on Machine Learning","number":504,"pages":{"first":3583,"last":3588},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}