Error-driven generalist+experts (edge): a multi-stage ensemble framework for text categorization
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[1] Susan T. Dumais,et al. Hierarchical classification of Web content , 2000, SIGIR '00.
[2] Kagan Tumer,et al. Analysis of decision boundaries in linearly combined neural classifiers , 1996, Pattern Recognit..
[3] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[4] M. Newman,et al. Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[5] Yiming Yang,et al. An Evaluation of Statistical Approaches to Text Categorization , 1999, Information Retrieval.
[6] Yiming Yang,et al. RCV1: A New Benchmark Collection for Text Categorization Research , 2004, J. Mach. Learn. Res..
[7] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[8] Fabrizio Sebastiani,et al. Machine learning in automated text categorization , 2001, CSUR.
[9] Omid Madani,et al. Large-Scale Many-Class Learning , 2008, SDM.
[10] Ryan M. Rifkin,et al. In Defense of One-Vs-All Classification , 2004, J. Mach. Learn. Res..
[11] Koby Crammer,et al. Online Passive-Aggressive Algorithms , 2003, J. Mach. Learn. Res..
[12] Mohammad R. Salavatipour,et al. Recall Systems: Effcient Learning and Use of Category Indices , 2007, AISTATS.
[13] Yoram Singer,et al. Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.
[14] Yoram Singer,et al. Using and combining predictors that specialize , 1997, STOC '97.
[15] F ROSENBLATT,et al. The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.
[16] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[17] William W. Cohen,et al. Single-pass online learning: performance, voting schemes and online feature selection , 2006, KDD '06.
[18] Susan T. Dumais,et al. Inductive learning algorithms and representations for text categorization , 1998, CIKM '98.
[19] Jian Huang,et al. On updates that constrain the features' connections during learning , 2008, KDD.
[20] S. Sathiya Keerthi,et al. A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs , 2005, J. Mach. Learn. Res..
[21] Kagan Tumer,et al. Robust Combining of Disparate Classifiers through Order Statistics , 1999, Pattern Analysis & Applications.
[22] David R. Karger,et al. Tackling the Poor Assumptions of Naive Bayes Text Classifiers , 2003, ICML.
[23] Adam Krzyżak,et al. Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..
[24] Koby Crammer,et al. A Family of Additive Online Algorithms for Category Ranking , 2003, J. Mach. Learn. Res..
[25] Chris Buckley,et al. OHSUMED: an interactive retrieval evaluation and new large test collection for research , 1994, SIGIR '94.
[26] Yoram Singer,et al. Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.
[27] Yiming Yang,et al. A scalability analysis of classifiers in text categorization , 2003, SIGIR.
[28] Yiming Yang,et al. Support vector machines classification with a very large-scale taxonomy , 2005, SKDD.
[29] Sunita Sarawagi,et al. Scaling multi-class support vector machines using inter-class confusion , 2002, KDD.
[30] Rich Caruana,et al. Data mining in metric space: an empirical analysis of supervised learning performance criteria , 2004, ROCAI.
[31] Andrea Esuli,et al. TreeBoost.MH: A Boosting Algorithm for Multi-label Hierarchical Text Categorization , 2006, SPIRE.
[32] Thomas Hofmann,et al. Hierarchical document categorization with support vector machines , 2004, CIKM '04.