We report on the development of a relational genomic search engine that integrates search of structured biological data and biomedical literature. After identifying an optimal prep...
The Multi-model search framework generalizes minimax to allow exploitation of recursive opponent models. In this work we consider adding pruning to the multi-model search. We prov...
In this paper we develop a methodology for defining stopping rules in a general class of global random search algorithms that are based on the use of statistical procedures. To bu...
In this paper we investigate how people use online rating information to inform decision making. We examine whether a theory of searching for information to discriminate between a...
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...