We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Anchor text has been shown to be effective in ranking[6] and a variety of information retrieval tasks on web pages. Some authors have expanded on anchor text by using the words ar...
This paper is to investigate rank aggregation based on multiple user-centered measures in the context of the web search. We introduce a set of techniques to combine ranking lists ...
Images and other high-dimensional data can frequently be characterized by a low dimensional manifold (e.g. one that corresponds to the degrees of freedom of the camera). Recently,...
Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale ...