Hyper-parameter optimization for support vector machines using stochastic gradient descent and dual coordinate descent
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[1] Fabian Pedregosa,et al. Hyperparameter optimization with approximate gradient , 2016, ICML.
[2] Jing Hu,et al. Bilevel Model Selection for Support Vector Machines , 2007 .
[3] Yasubumi Sakakibara,et al. Gradient-based optimization of hyperparameters for base-pairing profile local alignment kernels. , 2009, Genome informatics. International Conference on Genome Informatics.
[4] Nicolas P. Couellan. On the convergence of stochastic bi-level gradient methods , 2016 .
[5] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[6] Michael St. Jules. Experiments With Scalable Gradient-based Hyperparameter Optimization for Deep Neural Networks by , 2017 .
[7] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[8] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[9] Chuan-Sheng Foo,et al. Efficient multiple hyperparameter learning for log-linear models , 2007, NIPS.
[10] Elliot Meyerson,et al. Evolving Deep Neural Networks , 2017, Artificial Intelligence in the Age of Neural Networks and Brain Computing.
[11] I. Shpitser,et al. Machine Learning Methods Uncover Radiomorphologic Dose Patterns in Salivary Glands that Predict Xerostomia in Patients with Head and Neck Cancer , 2018, Advances in radiation oncology.
[12] J. Platt. Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .
[13] Goldberg,et al. Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.
[14] Dan Boneh,et al. On genetic algorithms , 1995, COLT '95.
[15] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[16] Jorge Nocedal,et al. Optimization Methods for Large-Scale Machine Learning , 2016, SIAM Rev..
[17] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[18] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2011, Math. Program..
[19] Ryan P. Adams,et al. Gradient-based Hyperparameter Optimization through Reversible Learning , 2015, ICML.
[20] Robert Tibshirani,et al. The Entire Regularization Path for the Support Vector Machine , 2004, J. Mach. Learn. Res..
[21] Kian Hsiang Low,et al. DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks , 2016, IJCAI.
[22] Paolo Frasconi,et al. Forward and Reverse Gradient-Based Hyperparameter Optimization , 2017, ICML.
[23] Jing Hu,et al. Bilevel Optimization and Machine Learning , 2008, WCCI.
[24] Nicolas Couellan,et al. Bi-level stochastic gradient for large scale support vector machine , 2015, Neurocomputing.
[25] Tong Zhang,et al. Solving large scale linear prediction problems using stochastic gradient descent algorithms , 2004, ICML.
[26] I. Shpitser,et al. Dose/Volume histogram patterns in Salivary Gland subvolumes influence xerostomia injury and recovery , 2019, Scientific Reports.
[27] Chih-Jen Lin,et al. A dual coordinate descent method for large-scale linear SVM , 2008, ICML '08.
[28] H. L. Le Roy,et al. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .
[29] J. Mockus. Bayesian Approach to Global Optimization: Theory and Applications , 1989 .