Heterogeneous cross domain ranking in latent space
暂无分享,去创建一个
Wei Fan | Jie Tang | Bo Wang | Songcan Chen | Yanzhu Liu | Zi Yang
[1] M Mitchell. On the other side. , 1994, Nursing.
[2] Daphne Koller,et al. Learning a meta-level prior for feature relevance from multiple related tasks , 2007, ICML '07.
[3] Rong Jin,et al. Semi-Supervised Ensemble Ranking , 2008, AAAI.
[4] Jie Tang,et al. ArnetMiner: extraction and mining of academic social networks , 2008, KDD.
[5] Jiawei Han,et al. Knowledge transfer via multiple model local structure mapping , 2008, KDD.
[6] Qiang Yang,et al. Boosting for transfer learning , 2007, ICML '07.
[7] Bo Wang,et al. Expert2Bólè: From Expert Finding to Bólè Search , 2009 .
[8] Kunle Olukotun,et al. Map-Reduce for Machine Learning on Multicore , 2006, NIPS.
[9] Thorsten Joachims,et al. Learning to classify text using support vector machines - methods, theory and algorithms , 2002, The Kluwer international series in engineering and computer science.
[10] Gregory N. Hullender,et al. Learning to rank using gradient descent , 2005, ICML.
[11] Tao Qin,et al. LETOR: Benchmark Dataset for Research on Learning to Rank for Information Retrieval , 2007 .
[12] Luis Mateus Rocha,et al. Singular value decomposition and principal component analysis , 2003 .
[13] Edwin V. Bonilla,et al. Multi-task Gaussian Process Prediction , 2007, NIPS.
[14] Tony Jebara,et al. Multi-task feature and kernel selection for SVMs , 2004, ICML.
[15] John D. Lafferty,et al. Model-based feedback in the language modeling approach to information retrieval , 2001, CIKM '01.
[16] Juan-Zi Li,et al. Expert Finding in a Social Network , 2007, DASFAA.
[17] Filip Radlinski,et al. A support vector method for optimizing average precision , 2007, SIGIR.
[18] Massimiliano Pontil,et al. Multi-Task Feature Learning , 2006, NIPS.
[19] Hang Li,et al. AdaRank: a boosting algorithm for information retrieval , 2007, SIGIR.
[20] Kevin Duh,et al. Learning to rank with partially-labeled data , 2008, SIGIR '08.
[21] Jieping Ye,et al. Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization , 2009, UAI.
[22] Koby Crammer,et al. Learning Bounds for Domain Adaptation , 2007, NIPS.
[23] Rajat Raina,et al. Self-taught learning: transfer learning from unlabeled data , 2007, ICML '07.
[24] Thorsten Joachims,et al. Training linear SVMs in linear time , 2006, KDD '06.
[25] Massih-Reza Amini,et al. A boosting algorithm for learning bipartite ranking functions with partially labeled data , 2008, SIGIR '08.
[26] Jaana Kekäläinen,et al. IR evaluation methods for retrieving highly relevant documents , 2000, SIGIR '00.
[27] John Blitzer,et al. Domain Adaptation with Structural Correspondence Learning , 2006, EMNLP.
[28] Thore Graepel,et al. Large Margin Rank Boundaries for Ordinal Regression , 2000 .
[29] Steffen Bickel,et al. Discriminative learning for differing training and test distributions , 2007, ICML '07.
[30] Tie-Yan Liu,et al. Learning to rank for information retrieval (LR4IR 2007) , 2007, SIGF.
[31] Larry P. Heck,et al. Trada: tree based ranking function adaptation , 2008, CIKM '08.
[32] Ulf Brefeld,et al. {AUC} maximizing support vector learning , 2005 .