Collaborative learning by boosting in distributed environments
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[1] Peter L. Bartlett,et al. Functional Gradient Techniques for Combining Hypotheses , 2000 .
[2] Nitesh V. Chawla,et al. Learning Ensembles from Bites: A Scalable and Accurate Approach , 2004, J. Mach. Learn. Res..
[3] Vipin Kumar,et al. Parallel formulations of decision-tree classification algorithms , 1998, Proceedings. 1998 International Conference on Parallel Processing (Cat. No.98EX205).
[4] Thomas G. Dietterich. Machine-Learning Research , 1997, AI Mag..
[5] Zoran Obradovic,et al. The distributed boosting algorithm , 2001, KDD '01.
[6] Eric Bauer,et al. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants , 1999, Machine Learning.
[7] Mark E. J. Newman,et al. The Structure and Function of Complex Networks , 2003, SIAM Rev..
[8] Vasant Honavar,et al. A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees , 2004, Int. J. Hybrid Intell. Syst..
[9] Changshui Zhang,et al. Network Game and Boosting , 2005, ECML.
[10] Foster J. Provost,et al. A Survey of Methods for Scaling Up Inductive Algorithms , 1999, Data Mining and Knowledge Discovery.
[11] Jiming Liu,et al. Autonomy-Oriented Social Networks Modeling: Discovering the Dynamics of Emergent Structure and Performance , 2007, Int. J. Pattern Recognit. Artif. Intell..
[12] Salvatore J. Stolfo,et al. The application of AdaBoost for distributed, scalable and on-line learning , 1999, KDD '99.
[13] Leo Breiman,et al. Pasting Small Votes for Classification in Large Databases and On-Line , 1999, Machine Learning.
[14] Yoav Freund,et al. Boosting the margin: A new explanation for the effectiveness of voting methods , 1997, ICML.
[15] Vipin Kumar,et al. Parallel Formulations of Decision-Tree Classification Algorithms , 2004, Data Mining and Knowledge Discovery.
[16] Naonori Ueda,et al. Generalization error of ensemble estimators , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).
[17] Xin Yao,et al. Diversity creation methods: a survey and categorisation , 2004, Inf. Fusion.
[18] Robert E. Schapire,et al. A Brief Introduction to Boosting , 1999, IJCAI.
[19] Qiang Yang,et al. Boosting for transfer learning , 2007, ICML '07.
[20] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[21] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[22] Thomas G. Dietterich. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization , 2000, Machine Learning.
[23] Alex Arenas,et al. Paths to synchronization on complex networks. , 2006, Physical review letters.
[24] Ron Kohavi,et al. Bias Plus Variance Decomposition for Zero-One Loss Functions , 1996, ICML.
[25] Zoran Obradovic,et al. Boosting Algorithms for Parallel and Distributed Learning , 2022 .