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...
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Han...
This poster describes an integrated set of stories and story-based activities that we have used in product development in IBM Software Group's Lotus product organizations. We...
Majie Zeller, Sandra L. Kogan, Michael J. Muller, ...
Relevance heuristics allow us to tailor a program analysis to a particular property to be verified. This in turn makes it possible to improve the precision of the analysis where n...
We present a verified compiler to an idealized assembly language from a small, untyped functional language with mutable references and exceptions. The compiler is programmed in th...