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ICML
2005
IEEE
14 years 9 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
ICADL
2004
Springer
137views Education» more  ICADL 2004»
14 years 2 months ago
Using Content-Based and Link-Based Analysis in Building Vertical Search Engines
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content a...
Michael Chau, Hsinchun Chen
ICAISC
2004
Springer
14 years 2 months ago
Comparison of Instances Seletion Algorithms I. Algorithms Survey
Abstract. Several methods were proposed to reduce the number of instances (vectors) in the learning set. Some of them extract only bad vectors while others try to remove as many in...
Norbert Jankowski, Marek Grochowski
ICANN
2003
Springer
14 years 1 months ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu
SEAL
1998
Springer
14 years 27 days ago
Co-evolution, Determinism and Robustness
Abstract. Robustness has long been recognised as a critical issue for coevolutionary learning. It has been achieved in a number of cases, though usually in domains which involve so...
Alan D. Blair, Elizabeth Sklar, Pablo Funes