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» Efficient learning equilibrium
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94
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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
15 years 10 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...
82
Voted
ITS
2004
Springer
99views Multimedia» more  ITS 2004»
15 years 3 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
87
Voted
IJCAI
2003
14 years 11 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, ...
112
Voted
JMLR
2008
230views more  JMLR 2008»
14 years 10 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...
87
Voted
ICCV
2009
IEEE
16 years 3 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...