We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
In this paper, a combinatorial auction problem is modeled as a NP-complete set packing problem and a Lagrangian relaxation based heuristic algorithm is proposed. Extensive experim...
Yunsong Guo, Andrew Lim, Brian Rodrigues, Jiqing T...
In this paper, we consider the recognition problem on the HHDS-free graphs, a class of homogeneously orderable graphs, and we show that it has polynomial time complexity. In partic...
Presented here is a generalization of the modified relative Newton method, recently proposed in [1] for quasi-maximum likelihood blind source separation. Special structure of the ...
Alexander M. Bronstein, Michael M. Bronstein, Mich...
Abstract. Monte-Carlo tree search, especially the UCT algorithm and its enhancements, have become extremely popular. Because of the importance of this family of algorithms, a deepe...