Semi‐supervised Learning Based on Distributionally Robust Optimization
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[1] Ronald Rosenfeld,et al. Semi-supervised learning with graphs , 2005 .
[2] Yoav Freund,et al. Scalable Semi-Supervised Aggregation of Classifiers , 2015, NIPS.
[3] Peter W. Glynn,et al. Unbiased Estimation with Square Root Convergence for SDE Models , 2015, Oper. Res..
[4] Daniel Kuhn,et al. Distributionally Robust Logistic Regression , 2015, NIPS.
[5] Yoshua Bengio,et al. Semi-supervised Learning by Entropy Minimization , 2004, CAP.
[6] Marco Loog,et al. Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Henry Lam,et al. The empirical likelihood approach to quantifying uncertainty in sample average approximation , 2017, Oper. Res. Lett..
[8] Bernhard Schölkopf,et al. Introduction to Semi-Supervised Learning , 2006, Semi-Supervised Learning.
[9] E. Polak. Introduction to linear and nonlinear programming , 1973 .
[10] Vishal Gupta,et al. Data-driven robust optimization , 2013, Math. Program..
[11] Avrim Blum,et al. Learning from Labeled and Unlabeled Data using Graph Mincuts , 2001, ICML.
[12] Yuanqing Li,et al. A self-training semi-supervised SVM algorithm and its application in an EEG-based brain computer interface speller system , 2008, Pattern Recognit. Lett..
[13] Don McLeish,et al. A general method for debiasing a Monte Carlo estimator , 2010, Monte Carlo Methods Appl..
[14] Yinyu Ye,et al. Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems , 2010, Oper. Res..
[15] C. Villani. Optimal Transport: Old and New , 2008 .
[16] O. Chapelle,et al. Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews] , 2009, IEEE Transactions on Neural Networks.
[17] Alexander Shapiro,et al. Lectures on Stochastic Programming: Modeling and Theory , 2009 .
[18] Shie Mannor,et al. Robust Regression and Lasso , 2008, IEEE Transactions on Information Theory.
[19] Peter W. Glynn,et al. Unbiased Monte Carlo for optimization and functions of expectations via multi-level randomization , 2015, 2015 Winter Simulation Conference (WSC).
[20] Constantine Caramanis,et al. Theory and Applications of Robust Optimization , 2010, SIAM Rev..
[21] Michael B. Giles,et al. Multilevel Monte Carlo Path Simulation , 2008, Oper. Res..
[22] Yang Kang,et al. Sample Out-of-Sample Inference Based on Wasserstein Distance , 2016, Oper. Res..
[23] M. KarthyekRajhaaA.,et al. Robust Wasserstein profile inference and applications to machine learning , 2019, J. Appl. Probab..
[24] Leonidas J. Guibas,et al. The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.
[25] Angelia Nedic,et al. Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization , 2008, J. Optim. Theory Appl..