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references.bib
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@book{barber2012bayesian,
title={Bayesian reasoning and machine learning},
author={Barber, David},
year={2012},
publisher={Cambridge University Press}
}
@book{cristianini2000introduction,
title={An Introduction To Support Vector Machines And Other Kernel-Based Learning Methods},
author={N. Cristianini and J. Shawe-Taylor},
year={2000},
publisher={Cambridge University Press}
}
@article{fan2008liblinear,
title={{LIBLINEAR: A Library for Large Linear Classification}},
author={R.E. Fan and K.W. Chang and C.J. Hsieh and X.R. Wang and C.J. Lin},
journal={The Journal of Machine Learning Research},
volume={9},
pages={1871--1874},
year={2008}
}
@book{Rasmussen2005GPM,
author = {Rasmussen, C. E. and Williams, C. K. I.},
title = {Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)},
year = {2005},
publisher = {The MIT Press},
year={2008},
}
@article{gretton2012kernel,
title={A kernel two-sample test},
author={Gretton, A. and Borgwardt, K.M. and Rasch, M.J. and Sch{\"o}lkopf, B. and Smola, A.},
journal={The Journal of Machine Learning Research},
volume={13},
number={1},
pages={723--773},
year={2012},
}
@article{ueda2000smem,
title={SMEM Algorithm for Mixture Models},
author={N. Ueda and R. Nakano and Z. Ghahramani and G.E. Hinton},
journal={Neural Computation},
volume={12},
number={9},
pages={2109--2128},
year={2000},
publisher={MIT Press}
}
@article{chang2011libsvm,
title={LIBSVM: a library for support vector machines},
author={C.C. Chang and C.J. Lin},
journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
volume={2},
number={3},
pages={27},
year={2011},
publisher={ACM}
}
@article{chang2002training,
title={Training v-support vector regression: theory and algorithms},
author={C.C. Chang and C.B. Lin},
journal={Neural Computation},
volume={14},
number={8},
pages={1959--1977},
year={2002},
publisher={MIT Press}
}
@book{scholkopf2002learning,
title={Learning with kernels: support vector machines, regularization, optimization, and beyond},
author={B. Sch{\"o}lkopf and A.J. Smola},
year={2002},
publisher={MIT press}
}
@unpublished{Goodfellow-et-al-2016-Book,
title={Deep Learning},
author={I. Goodfellow and Y. Bengio and A. Courville},
note={Book in preparation for MIT Press},
year={2016}
}
@article{escalera2010error,
title={Error-correcting ouput codes library},
author={S. Escalera and O. Pujol and P. Radeva},
journal={The Journal of Machine Learning Research},
volume={11},
pages={661--664},
year={2010},
publisher={JMLR. org}
}
@inproceedings{gao2011discriminative,
title={Discriminative learning of relaxed hierarchy for large-scale visual recognition},
author={T. Gao and D. Koller},
booktitle={2011 IEEE International Conference on Computer Vision},
pages={2072--2079},
year={2011},
organization={IEEE}
}
@inproceedings{shalev2011shareboost,
title={Shareboost: Efficient multiclass learning with feature sharing},
author={S. Shalev-Shwartz and Y. Wexler and A. Shashua},
booktitle={Advances in Neural Information Processing Systems},
pages={1179--1187},
year={2011}
}
@inproceedings{gretton2012optimal,
author={Gretton, A. and Sriperumbudur, B. and Sejdinovic, D. and Strathmann, H. and Balakrishnan, S. and Pontil, M. and Fukumizu, K.},
booktitle={Advances in Neural Information Processing Systems},
title={{Optimal kernel choice for large-scale two-sample tests}},
year={2012}
}
@article{sonnenburg2006large,
title={Large scale multiple kernel learning},
author={S. Sonnenburg and G. R{\"a}tsch and C. Sch{\"a}fer and B. Sch{\"o}lkopf},
journal={The Journal of Machine Learning Research},
volume={7},
pages={1531--1565},
year={2006},
publisher={JMLR.org}
}