暂无分享,去创建一个
Bernhard Schölkopf | David Lopez-Paz | Vladimir Vapnik | Léon Bottou | L. Bottou | B. Schölkopf | V. Vapnik | David Lopez-Paz | B. Scholkopf
[1] Bernhard Schölkopf,et al. Improving the accuracy and speed of support vector learning machines , 1997, NIPS 1997.
[2] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[3] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[4] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[5] Rich Caruana,et al. Model compression , 2006, KDD '06.
[6] Jason Weston,et al. Inference with the Universum , 2006, ICML.
[7] Bernhard Schölkopf,et al. An Analysis of Inference with the Universum , 2007, NIPS.
[8] Vladimir Vapnik,et al. A new learning paradigm: Learning using privileged information , 2009, Neural Networks.
[9] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[10] V. Vapnik,et al. On the theory of learning with Privileged Information , 2010, NIPS 2010.
[11] Bernhard Schölkopf,et al. Causal Inference Using the Algorithmic Markov Condition , 2008, IEEE Transactions on Information Theory.
[12] Bernardete Ribeiro,et al. Financial distress model prediction using SVM+ , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[13] Uwe Aickelin,et al. Privileged information for data clustering , 2012, Inf. Sci..
[14] Bernhard Schölkopf,et al. On causal and anticausal learning , 2012, ICML.
[15] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[16] Christoph H. Lampert,et al. Learning to Rank Using Privileged Information , 2013, 2013 IEEE International Conference on Computer Vision.
[17] Peter Tiño,et al. Incorporating Privileged Information Through Metric Learning , 2013, IEEE Transactions on Neural Networks and Learning Systems.
[18] Léon Bottou,et al. From machine learning to machine reasoning , 2011, Machine Learning.
[19] Bernhard Schölkopf,et al. Randomized Nonlinear Component Analysis , 2014, ICML.
[20] Christoph H. Lampert,et al. Mind the Nuisance: Gaussian Process Classification using Privileged Noise , 2014, NIPS.
[21] Ivan Laptev,et al. Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[22] Christoph H. Lampert,et al. Learning to Transfer Privileged Information , 2014, ArXiv.
[23] Bernt Schiele,et al. Learning using privileged information: SV M+ and weighted SVM , 2013, Neural Networks.
[24] Rich Caruana,et al. Do Deep Nets Really Need to be Deep? , 2013, NIPS.
[25] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[26] Rauf Izmailov,et al. Learning using privileged information: similarity control and knowledge transfer , 2015, J. Mach. Learn. Res..
[27] Xinyun Chen. Under Review as a Conference Paper at Iclr 2017 Delving into Transferable Adversarial Ex- Amples and Black-box Attacks , 2016 .
[28] Omer Levy,et al. Published as a conference paper at ICLR 2018 S IMULATING A CTION D YNAMICS WITH N EURAL P ROCESS N ETWORKS , 2018 .