Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
Accurately aligning distant protein sequences is notoriously difficult. A recent approach to improving alignment accuracy is to use additional information such as predicted seconda...
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s langu...
Tiling is a widely used loop transformation for exposing/exploiting parallelism and data locality. Effective use of tiling requires selection and tuning of the tile sizes. This is...
Credit assignment is a fundamental issue for the Learning Classifier Systems literature. We engage in a detailed investigation of credit assignment in one recent system called UC...