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SIGIR
2002
ACM
15 years 4 months ago
A new family of online algorithms for category ranking
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Koby Crammer, Yoram Singer
CORR
2002
Springer
86views Education» more  CORR 2002»
15 years 4 months ago
The Management of Context-Sensitive Features: A Review of Strategies
In this paper, we review five heuristic strategies for handling context-sensitive features in supervised machine learning from examples. We discuss two methods for recovering lost...
Peter D. Turney
167
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WWW
2008
ACM
16 years 5 months ago
First workshop on targeting and ranking for online advertising
Online advertising is a rapidly growing, multi-billion dollar industry. It has become a significant element of the Web browsing experience. Ad platforms used for ad selection use ...
Ewa Dominowska, Vanja Josifovski
MCS
2010
Springer
15 years 10 months ago
Online Non-stationary Boosting
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
CSCW
2012
ACM
14 years 18 days ago
Organizing without formal organization: group identification, goal setting and social modeling in directing online production
A challenge for many online production communities is to direct their members to accomplish tasks that are important to the group, even when these tasks may not match individual m...
Haiyi Zhu, Robert Kraut, Aniket Kittur