— Rapidly-exploring Random Trees (RRTs) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but the efficiency o...
Alexander C. Shkolnik, Matthew Walter, Russ Tedrak...
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
Decision tree-based probability estimation has received great attention because accurate probability estimation can possibly improve classification accuracy and probability-based r...
As the Extensible Markup Language (XML) rapidly establishes itself as the de facto standard for presenting, storing, and exchanging data on the Internet, large volume of XML data ...
Computational diagnosis of cancer is a classification problem, and it has two special requirements on a learning algorithm: perfect accuracy and small number of features used in t...