Why can multi-task learning be a good solution? On one hand, compared to separate learning for each task, by grouping the training data of several tasks, we have a larger amount of training data. If the underlying characteristics among the training data are similar, the resulting ranking functions can be better.
Nov 6, 2009
▻ We propose a novel algorithm to learn multiple ranking functions simultaneously. ▻ It adaptively learns super-features among multiple tasks in a stage-wise ...
Nov 2, 2009 · We evaluate the performance of this multi-task learning method for web search ranking using data from a search engine. Our results demonstrate ...
We propose a multi-task learning framework to jointly learn document ranking and query suggestion for web search. It consists of two major components, ...
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We evaluate the accuracy of multi-task learning methods for web search ranking using data from multiple domains from a commercial search engine. Our results ...
We conduct a comprehensive set of experiments on a real- world product search dataset in e-commerce and show the effectiveness of the proposed approach over the ...
The multi-task boosting method has been proposed for learning web search ranking [50] by sharing feature representation between various tasks. In [51] matrix ...
Nov 2, 2009 · We evaluate the performance of this multi-task learning method for web search ranking using data from a search engine. Our results demonstrate ...
A general framework for feature selection in learning to rank using support vector machines with a sparse regularization term is proposed and it is shown ...
Multi-Task Learning for Boosting with Application to Web Search Ranking, KDD 2010. Proceedings of the 16th international conference on Knowledge discovery and ...