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» A Bayesian Approximation Method for Online Ranking
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ICCV
2005
IEEE
14 years 1 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
WWW
2008
ACM
14 years 8 months ago
Analyzing search engine advertising: firm behavior and cross-selling in electronic markets
The phenomenon of sponsored search advertising is gaining ground as the largest source of revenues for search engines. Firms across different industries have are beginning to adop...
Anindya Ghose, Sha Yang
CIKM
2008
Springer
13 years 9 months ago
Efficient sampling of information in social networks
As online social networking emerges, there has been increased interest to utilize the underlying social structure as well as the available social information to improve search. In...
Gautam Das, Nick Koudas, Manos Papagelis, Sushruth...
CIKM
2009
Springer
14 years 2 months ago
Post-rank reordering: resolving preference misalignments between search engines and end users
No search engine is perfect. A typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higherrank...
Chao Liu, Mei Li, Yi-Min Wang