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![]() Date: 2016-06-28 04:30:57Machine learning Learning Learning to rank Ranking SVM Support vector machine PageRank Ranking Stability Document retrieval Information retrieval Feature selection Supervised learning | Add to Reading List |
![]() | Microsoft Word - LR4IR2009.v4-camera-nomark.docDocID: 1pnMD - View Document |
![]() | Nonlinear Feature Selection with the Potential Support Vector Machine Sepp Hochreiter and Klaus Obermayer Technische Universit¨ at Berlin Fakult¨DocID: 1p8pc - View Document |
![]() | Metric Learning to Rank Brian McFee Department of Computer Science and Engineering, University of California, San Diego, CAUSA Gert LanckrietDocID: 1oZVx - View Document |
![]() | Perturbation based Large Margin Approach for Ranking Eunho Yang University of Texas at Austin Ambuj TewariDocID: 1m9Nw - View Document |
![]() | Noname manuscript No. (will be inserted by the editor) Learning to Rank with (a Lot of ) Word Features Bing Bai · Jason Weston · David Grangier · Ronan Collobert · Kunihiko Sadamasa ·DocID: 19Cff - View Document |