[PDF][PDF] Ranked bandits in metric spaces: learning diverse rankings over large document collections
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
A Slivkins, F Radlinski, S Gollapudi - Journal of Machine Learning …, 2013 - jmlr.org
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
[PDF][PDF] Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
A Slivkins, F Radlinski, S Gollapudi - Journal of Machine Learning …, 2013 - jmlr.csail.mit.edu
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked bandits in metric spaces: learning optimally diverse rankings over large document collections
A Slivkins, F Radlinski, S Gollapudi - arXiv e-prints, 2010 - ui.adsabs.harvard.edu
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections.
A Slivkins, F Radlinski… - Journal of Machine …, 2013 - search.ebscohost.com
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked bandits in metric spaces: learning optimally diverse rankings over large document collections
A Slivkins, F Radlinski, S Gollapudi - arXiv preprint arXiv:1005.5197, 2010 - arxiv.org
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked bandits in metric spaces: learning diverse rankings over large document collections
A Slivkins, F Radlinski, S Gollapudi - The Journal of Machine Learning …, 2013 - dl.acm.org
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
[PDF][PDF] Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
A Slivkins, F Radlinski, S Gollapudi - Journal of Machine Learning …, 2013 - Citeseer
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
A Slivkins, F Radlinski, S Gollapudi - Journal of Machine Learning …, 2013 - jmlr.csail.mit.edu
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections.
A Slivkins, F Radlinski… - Journal of Machine …, 2013 - search.ebscohost.com
Most learning to rank research has assumed that the utility of different documents is
independent, which results in learned ranking functions that return redundant results. The …
independent, which results in learned ranking functions that return redundant results. The …