of the 2015 ChaLeam AutoML Challenge
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Isabelle Guyon | Gavin C. Cawley | Hugo Jair Escalante | Núria Macià | Kristin P. Bennett | Evelyne Viegas | Mehreen Saeed | Bisakha Ray | Alexander Statnikov | Escalera Tin | Kam Ho | I. Guyon | K. Bennett | H. Escalante | A. Statnikov | E. Viegas | G. Cawley | Bisakha Ray | Núria Macià | M. Saeed | Kristin P. Bennett | Escalera Tin | Kam Ho | I. Ramadass Subramanian | Isabelle M Guyon
[1] Bracha Shapira,et al. Recommender Systems Handbook , 2015, Springer US.
[2] Jasper Snoek,et al. Multi-Task Bayesian Optimization , 2013, NIPS.
[3] Michael I. Jordan. On statistics, computation and scalability , 2013, ArXiv.
[4] Michèle Sebag,et al. Collaborative hyperparameter tuning , 2013, ICML.
[5] David D. Cox,et al. Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures , 2013, ICML.
[6] Kevin Leyton-Brown,et al. Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms , 2012, KDD.
[7] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Tom Schaul,et al. No more pesky learning rates , 2012, ICML.
[9] Quan Sun,et al. Full model selection in the space of data mining operators , 2012, GECCO '12.
[10] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[11] Yoshua Bengio,et al. Algorithms for Hyper-Parameter Optimization , 2011, NIPS.
[12] Kristin P. Bennett,et al. Model selection for primal SVM , 2011, Machine Learning.
[13] Kevin Leyton-Brown,et al. Sequential Model-Based Optimization for General Algorithm Configuration , 2011, LION.
[14] Isabelle Guyon,et al. Model Selection: Beyond the Bayesian/Frequentist Divide , 2010, J. Mach. Learn. Res..
[15] Hugo Jair Escalante,et al. Particle Swarm Model Selection , 2009, J. Mach. Learn. Res..
[16] Constantin F. Aliferis,et al. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification , 2008, BMC Bioinformatics.
[17] Gavin C. Cawley,et al. Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters , 2007, J. Mach. Learn. Res..
[18] S. Sathiya Keerthi,et al. An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models , 2006, NIPS.
[19] Masoud Nikravesh,et al. Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing) , 2006 .
[20] Robert Tibshirani,et al. The Entire Regularization Path for the Support Vector Machine , 2004, J. Mach. Learn. Res..
[21] Rich Caruana,et al. Ensemble selection from libraries of models , 2004, ICML.
[22] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[23] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[24] Bernhard Schölkopf,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2005, IEEE Transactions on Neural Networks.
[25] Kristin P. Bennett,et al. A Pattern Search Method for Model Selection of Support Vector Regression , 2002, SDM.
[26] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[27] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[28] A. Doucet,et al. Sequential MCMC for Bayesian model selection , 1999, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics. SPW-HOS '99.
[29] Pat Langley,et al. Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..
[30] Ron Kohavi,et al. Wrappers for feature selection , 1997 .
[31] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[32] H. B. Barlow,et al. Unsupervised Learning , 1989, Neural Computation.
[33] B. Efron. Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation , 1983 .