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WWW
2007
ACM
16 years 7 months ago
Supervised rank aggregation
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Han...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 6 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
ITS
2004
Springer
99views Multimedia» more  ITS 2004»
15 years 11 months ago
Promoting Effective Help-Seeking Behavior Through Declarative Instruction
The ability to use help-resources efficiently is an important skill in any learning environment, whether the student is in a traditional classroom or is using an Intelligent Tutor...
Ido Roll, Vincent Aleven, Kenneth R. Koedinger
IJCAI
2003
15 years 7 months ago
Spaces of Theories with Ideal Refinement Operators
Refinement operators for theories avoid the problems related to the myopia of many relational learning algorithms based on the operators that refine single clauses. However, the n...
Nicola Fanizzi, Stefano Ferilli, Nicola Di Mauro, ...
JMLR
2008
230views more  JMLR 2008»
15 years 6 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...