Multiple Classifier Systems

[1]  Min-Ling Zhang,et al.  A Review on Multi-Label Learning Algorithms , 2014, IEEE Transactions on Knowledge and Data Engineering.

[2]  Miao Xu,et al.  Multi-Label Learning with PRO Loss , 2013, AAAI.

[3]  Zhi-Hua Zhou,et al.  Selective Ensemble of Classifier Chains , 2013, MCS.

[4]  Nan Ye,et al.  Optimizing F-measure: A Tale of Two Approaches , 2012, ICML.

[5]  Zhi-Hua Zhou,et al.  Ensemble Methods: Foundations and Algorithms , 2012 .

[6]  Zhi-Hua Zhou,et al.  On the Consistency of Multi-Label Learning , 2011, COLT.

[7]  Philip S. Yu,et al.  Multi-label Ensemble Learning , 2011, ECML/PKDD.

[8]  Rong Jin,et al.  Multi-label learning with incomplete class assignments , 2011, CVPR 2011.

[9]  Grigorios Tsoumakas,et al.  MULAN: A Java Library for Multi-Label Learning , 2011, J. Mach. Learn. Res..

[10]  Geoff Holmes,et al.  Classifier chains for multi-label classification , 2009, Machine Learning.

[11]  Eyke Hüllermeier,et al.  Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss , 2010, ECML/PKDD.

[12]  Kun Zhang,et al.  Multi-label learning by exploiting label dependency , 2010, KDD.

[13]  Eyke Hüllermeier,et al.  Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains , 2010, ICML.

[14]  Lihi Zelnik-Manor,et al.  Large Scale Max-Margin Multi-Label Classification with Priors , 2010, ICML.

[15]  Zhi-Hua Zhou,et al.  Selective Ensemble under Regularization Framework , 2009, MCS.

[16]  John Langford,et al.  Multi-Label Prediction via Compressed Sensing , 2009, NIPS.

[17]  S. Shalev-Shwartz,et al.  Stochastic methods for {\it l}$_{\mbox{1}}$ regularized loss minimization , 2009, ICML 2009.

[18]  Geoff Holmes,et al.  Multi-label Classification Using Ensembles of Pruned Sets , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[19]  Eyke Hüllermeier,et al.  Multilabel classification via calibrated label ranking , 2008, Machine Learning.

[20]  Chih-Jen Lin,et al.  LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..

[21]  Gert R. G. Lanckriet,et al.  Semantic Annotation and Retrieval of Music and Sound Effects , 2008, IEEE Transactions on Audio, Speech, and Language Processing.

[22]  Grigorios Tsoumakas,et al.  Random k -Labelsets: An Ensemble Method for Multilabel Classification , 2007, ECML.

[23]  Filip Radlinski,et al.  A support vector method for optimizing average precision , 2007, SIGIR.

[24]  Zhi-Hua Zhou,et al.  ML-KNN: A lazy learning approach to multi-label learning , 2007, Pattern Recognit..

[25]  Alexander J. Smola,et al.  Direct Optimization of Ranking Measures , 2007, ArXiv.

[26]  William Nick Street,et al.  Ensemble Pruning Via Semi-definite Programming , 2006, J. Mach. Learn. Res..

[27]  Thomas Hofmann,et al.  Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..

[28]  Andrew McCallum,et al.  Collective multi-label classification , 2005, CIKM '05.

[29]  Thorsten Joachims,et al.  A support vector method for multivariate performance measures , 2005, ICML.

[30]  Jiebo Luo,et al.  Learning multi-label scene classification , 2004, Pattern Recognit..

[31]  Yoram Singer,et al.  BoosTexter: A Boosting-based System for Text Categorization , 2000, Machine Learning.

[32]  Naonori Ueda,et al.  Parametric Mixture Models for Multi-Labeled Text , 2002, NIPS.

[33]  Fabio Roli,et al.  Design of effective multiple classifier systems by clustering of classifiers , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.