This paper presents a statistical model for expressing preferences through rankings, when the number of alternatives (items to rank) is large. A human ranker will then typically r...
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
Recently, many new applications, such as sensor data monitoring and mobile device tracking, raise up the issue of uncertain data management. Compared to "certain" data, ...
We propose a new ranking paradigm for relational databases called Structured Value Ranking (SVR). SVR uses structured data values to score (rank) the results of keyword search que...
Lin Guo, Jayavel Shanmugasundaram, Kevin S. Beyer,...