Feature Set Embedding for Incomplete Data
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[1] Pieter Abbeel,et al. Max-margin Classification of Data with Absent Features , 2008, J. Mach. Learn. Res..
[2] Hui Li,et al. Quadratically gated mixture of experts for incomplete data classification , 2007, ICML '07.
[3] Ji Zhu,et al. Margin Maximizing Loss Functions , 2003, NIPS.
[4] Naftali Tishby,et al. Learning to Select Features using their Properties , 2008 .
[5] Daphne Koller,et al. Learning Object Shape: From Drawings to Images , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[6] William Stafford Noble,et al. Predicting Co-Complexed Protein Pairs from Heterogeneous Data , 2008, PLoS Comput. Biol..
[7] Naum Zuselevich Shor,et al. Minimization Methods for Non-Differentiable Functions , 1985, Springer Series in Computational Mathematics.
[8] Hugo Larochelle,et al. Efficient Learning of Deep Boltzmann Machines , 2010, AISTATS.
[9] Gustavo E. A. P. A. Batista,et al. A Study of K-Nearest Neighbour as an Imputation Method , 2002, HIS.
[10] Peter Haider,et al. Learning from incomplete data with infinite imputations , 2008, ICML '08.
[11] Joseph L Schafer,et al. Analysis of Incomplete Multivariate Data , 1997 .
[12] Yves Grandvalet,et al. Noise Injection: Theoretical Prospects , 1997, Neural Computation.
[13] Lawrence Carin,et al. Incomplete-data classification using logistic regression , 2005, ICML.
[14] Y. Ermoliev,et al. Stochastic Generalized Gradient Method with Application to Insurance Risk Management , 1997 .
[15] Alexander J. Smola,et al. A Second Order Cone programming Formulation for Classifying Missing Data , 2004, NIPS.
[16] Tony Jebara,et al. A Kernel Between Sets of Vectors , 2003, ICML.
[17] Jason Weston,et al. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition , 2007, BMC Bioinformatics.
[18] Jean-Philippe Tarel,et al. Non-Mercer Kernels for SVM Object Recognition , 2004, BMVC.
[19] Michael I. Jordan,et al. Supervised learning from incomplete data via an EM approach , 1993, NIPS.
[20] Amir Globerson,et al. Nightmare at test time: robust learning by feature deletion , 2006, ICML.
[21] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.
[22] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[23] Ohad Shamir,et al. Learning to classify with missing and corrupted features , 2008, ICML.
[24] Rui Xu,et al. Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.
[25] Patrice Y. Simard,et al. Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..