We relate two problems that have been explored in two distinct communities. The first is the problem of combining expert advice, studied extensively in the computational learning...
Abstract. We study online regret minimization algorithms in a bicriteria setting, examining not only the standard notion of regret to the best expert, but also the regret to the av...
Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, ...
We argue that expert finding is sensitive to multiple document features in an organizational intranet. These document features include multiple levels of associations between expe...
Jianhan Zhu, Xiangji Huang, Dawei Song, Stefan M. ...
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
The University College London Information Retrieval Group participated in both the Expert Search and Document Search tasks in the TREC2008 Enterprise Track. We used a generic two-...