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» Learning to Rank Using an Ensemble of Lambda-Gradient Models
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IJCAI
2001
13 years 9 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost
DMIN
2008
190views Data Mining» more  DMIN 2008»
13 years 9 months ago
Optimization of Self-Organizing Maps Ensemble in Prediction
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Elie Prudhomme, Stéphane Lallich
IJON
2010
148views more  IJON 2010»
13 years 6 months ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
INFORMS
2007
123views more  INFORMS 2007»
13 years 7 months ago
Constructing Ensembles from Data Envelopment Analysis
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...
Zhiqiang Zheng, Balaji Padmanabhan
SIGIR
2008
ACM
13 years 7 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma