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» Evaluating learning algorithms and classifiers
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WWW
2007
ACM
16 years 5 months ago
Classifying web sites
In this paper, we present a novel method for the classification of Web sites. This method exploits both structure and content of Web sites in order to discern their functionality....
Christoph Lindemann, Lars Littig
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
15 years 11 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer
KDD
1998
ACM
84views Data Mining» more  KDD 1998»
15 years 8 months ago
Towards the Personalization of Algorithms Evaluation in Data Mining
Like model selectionin statistics,the choiceof appropriate Data Mining Algorithms (DM-Algorithms) is a very importanttask in the processof KnowledgeDiscovery.Due to this fact it i...
Gholamreza Nakhaeizadeh, Alexander Schnabl
CORR
2006
Springer
126views Education» more  CORR 2006»
15 years 4 months ago
Evaluating the Robustness of Learning from Implicit Feedback
This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory ...
Filip Radlinski, Thorsten Joachims
ICML
1996
IEEE
15 years 8 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos