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» A primal-dual perspective of online learning algorithms
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ML
2007
ACM
131views Machine Learning» more  ML 2007»
13 years 3 months ago
A primal-dual perspective of online learning algorithms
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
MCS
2010
Springer
13 years 8 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...
WWW
2008
ACM
14 years 4 months ago
Online learning from click data for sponsored search
Sponsored search is one of the enabling technologies for today's Web search engines. It corresponds to matching and showing ads related to the user query on the search engine...
Massimiliano Ciaramita, Vanessa Murdock, Vassilis ...
SOFSEM
2010
Springer
14 years 15 days ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour
UAI
1997
13 years 5 months ago
Update Rules for Parameter Estimation in Bayesian Networks
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Eric Bauer, Daphne Koller, Yoram Singer