This paper aims to tackle the very interesting and important problem of user personalized ranking of search results. The focus is on news retrieval and the data from which the ran...
Human action video sequences can be considered as nonlinear dynamic shape manifolds in the space of image frames. In this paper, we address learning and classifying human actions ...
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
Raj D. Iyer, David D. Lewis, Robert E. Schapire, Y...
The Random Projection Tree (RPTREE) structures proposed in [1] are space partitioning data structures that automatically adapt to various notions of intrinsic dimensionality of da...
To learn a metric for query?based operations, we combine the concept underlying manifold learning algorithms and the minimum volume ellipsoid metric in a unified algorithm to find...