论文标题
IPBOOST-通过整数编程来提高非convex
IPBoost -- Non-Convex Boosting via Integer Programming
论文作者
论文摘要
最近，用于解决机器学习问题的非凸优化方法已引起了很大的关注。在本文中，我们通过整数编程探讨了分类中的非凸增强，并证明了该方法的现实性实用性，同时绕过了增强凸的方法的缺点。我们报告的结果与当前最新的结果相当或更好。
Recently non-convex optimization approaches for solving machine learning problems have gained significant attention. In this paper we explore non-convex boosting in classification by means of integer programming and demonstrate real-world practicability of the approach while circumventing shortcomings of convex boosting approaches. We report results that are comparable to or better than the current state-of-the-art.
