资源论文Approximation Algorithms for Max-Sum-Product Problems

Approximation Algorithms for Max-Sum-Product Problems

2019-11-08 | |  87 |   41 |   0

Abstract Many tasks in probabilistic reasoning can be cast as max-sum-product problems, a hard class of combinatorial problems. We describe our results in obtaining a new approximation scheme for the problem, that can be turned into an anytime procedure. For many tasks, this scheme can be shown to be asymptotically the best possible heuristic.

上一篇:Concept Generation in Language Evolution

下一篇:Sparse Reconstruction for Weakly Supervised Semantic Segmentation

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...