references.bib

@string{aistats8 = {8th International Conference on Artificial Intelligence and Statistics}}
@string{aistats9 = {9th International Conference on Artificial Intelligence and Statistics}}
@string{aistats10 = {10th International Conference on Artificial Intelligence and Statistics}}
@string{aistats11 = {11th International Conference on Artificial Intelligence and Statistics}}
@string{aistats12 = {12th International Conference on Artificial Intelligence and Statistics}}
@string{aistats13 = {13th International Conference on Artificial Intelligence and Statistics}}
@string{aistats14 = {14th International Conference on Artificial Intelligence and Statistics}}
@string{aistats15 = {15th International Conference on Artificial Intelligence and Statistics}}
@string{aistats16 = {16th International Conference on Artificial Intelligence and Statistics}}
@string{aistats17 = {17th International Conference on Artificial Intelligence and Statistics}}
@string{icml20 = {20th International Conference on Machine Learning}}
@string{icml21 = {21st International Conference on Machine Learning}}
@string{icml22 = {22nd International Conference on Machine Learning}}
@string{icml23 = {23rd International Conference on Machine Learning}}
@string{icml24 = {24th International Conference on Machine Learning}}
@string{icml25 = {25th International Conference on Machine Learning}}
@string{icml26 = {26th International Conference on Machine Learning}}
@string{icml27 = {27th International Conference on Machine Learning}}
@string{icml28 = {28th International Conference on Machine Learning}}
@string{icml29 = {29th International Conference on Machine Learning}}
@string{icml30 = {30th International Conference on Machine Learning}}
@string{nips8  = {Advances in Neural Information Processing Systems 8}}
@string{nips9  = {Advances in Neural Information Processing Systems 9}}
@string{nips10 = {Advances in Neural Information Processing Systems 10}}
@string{nips11 = {Advances in Neural Information Processing Systems 11}}
@string{nips12 = {Advances in Neural Information Processing Systems 12}}
@string{nips13 = {Advances in Neural Information Processing Systems 13}}
@string{nips14 = {Advances in Neural Information Processing Systems 14}}
@string{nips15 = {Advances in Neural Information Processing Systems 15}}
@string{nips16 = {Advances in Neural Information Processing Systems 16}}
@string{nips17 = {Advances in Neural Information Processing Systems 17}}
@string{nips18 = {Advances in Neural Information Processing Systems 18}}
@string{nips19 = {Advances in Neural Information Processing Systems 19}}
@string{nips20 = {Advances in Neural Information Processing Systems 20}}
@string{nips21 = {Advances in Neural Information Processing Systems 21}}
@string{nips22 = {Advances in Neural Information Processing Systems 22}}
@string{nips23 = {Advances in Neural Information Processing Systems 23}}
@string{nips24 = {Advances in Neural Information Processing Systems 24}}
@string{nips25 = {Advances in Neural Information Processing Systems 25}}
@string{nips26 = {Advances in Neural Information Processing Systems 26}}
@string{nips27 = {Advances in Neural Information Processing Systems 27}}
@string{cogsci32 = {The Proceedings of the 32nd Annual Meeting of the Cognitive Science Society}}
@String{uai22 = {22nd Conference on Uncertainty in Artificial Intelligence}}
@String{uai27 = {27th Conference on Uncertainty in Artificial Intelligence}}
@String{uai28 = {28th Conference on Uncertainty in Artificial Intelligence}}
@String{uai29 = {29th Conference on Uncertainty in Artificial Intelligence}}

@string{cup    = {{C}ambridge {U}niversity Press}}
@string{curran = {Curran Associates, Inc.}}
@string{AAAI   = {AAAI Press}}
@string{mit    = {The {MIT} Press}}
@string{oup    = {{O}xford {U}niversity Press}}
@string{WILEY  = {John Wiley \& Sons}}
@String{rss9   = {9th International Conference on Robotics: Science \& Systems}}
@string{IECY   = {IEEE Transactions on System Science and Cybernetics}}
@string{IENN   = {IEEE Transactions on Neural Networks}}
@string{IETAC  = {IEEE Transactions on Automatic Control}}
@string{PAMI   = {IEEE Transactions on Pattern Analysis and Machine Intelligence}}
@string{tcbb   = {IEEE/ACM Transactions on Computational Biology and Bioinformatics}}
@string{jasa   = {Journal of the Americal Statistical Association}}
@string{jmlr   = {Journal of Machine Learning Research}}
@string{jrssB  = {Journal of the Royal Statistical Society, Series B}}
@string{jcst   = {Journal of Computer Science and Technology}}
@string{nc     = {Neural Computation}}
@string{PCPS   = {Proceedings of the Cambridge Philosophical Society}}
@string{tams   = {The Annals of Mathematical Statistics}}
@string{lncs   = {Lecture Notes in Computer Science (LNCS)}}



\% Very deep references

@Misc{ eamcblogWilk10,
	author = "Darren Wilkinson",
	title = "The pseudo-marginal approach to exact-approximate {MCMC} algorithms",
	type = "Blog",
	number = "September 20",
	year = "2010",
	howpublished = "http://darrenjw.wordpress.com/2010/09/20/the-pseudo-marginal-approach-to-exact-approximate-mcmc-algorithms/"
}

@inproceedings{IwaDuvGha12,
  author =	 {Tomoharu Iwata and David Duvenaud and Zoubin Ghahramani},
  title =	 {Warped Mixtures for Nonparametric Cluster Shapes},
  booktitle =	 uai29,
  address =	 {Bellevue, Washington},
  month =	 {July},
  year =	 2013
}

@inproceedings{DuvRipAdaGha14,
  title =	 {Avoiding pathologies in very deep networks},
  author =	 {David Duvenaud and Oren Rippel and Ryan P. Adams and Zoubin Ghahramani},
  booktitle =	 aistats17,
  year =	 2014,
  month =	 {April},
  address =	 {Reykjavik, Iceland}
}

@InProceedings{ adams2010learning,
	title = "Learning the Structure of Deep Sparse Graphical Models",
	author = "Ryan P. Adams and Hanna M. Wallach and Zoubin Ghahramani",
	booktitle = "Proceedings of the International Conference on Artificial Intelligence and Statistics",
	year = "2010"
}

@PhDThesis{ cho2012kernel,
	title = "Kernel methods for deep learning",
	author = "Youngmin Cho",
	year = "2012",
	school = "University of California, San Diego"
}

@PhDThesis{ neal1995bayesian,
	title = "{B}ayesian learning for neural networks",
	author = "Radford M. Neal",
	year = "1995",
	school = "University of Toronto"
}

@Article{ montavon2010layer,
	title = "Layer-wise analysis of deep networks with {G}aussian kernels",
	author = {Gr{\'e}goire Montavon and Mikio L. Braun and Klaus-Robert M{\"u}ller},
	journal = "Advances in Neural Information Processing Systems",
	volume = "23",
	pages = "1678--1686",
	year = "2010"
}

@InProceedings{ damianou2012deep,
	author = "Andreas Damianou and Neil D. Lawrence",
	title = "Deep {G}aussian Processes",
	booktitle = "Artificial Intelligence and Statistics",
	year = "2013",
	location = "Arizona, USA",
	pages = "207--215"
}

@InProceedings{ hensman2014deep,
	author = "James Hensman and Andreas Damianou and Neil D. Lawrence",
	title = "Deep {G}aussian Processes for Large Datasets",
	booktitle = "Artificial Intelligence and Statistics Late-breaking Posters",
	year = "2014",
	location = "Reykjavik, Iceland"
}

@InProceedings{ Solak03derivativeobservations,
	author = "Ercan Solak and Roderick Murray-Smith and William E. Leithead and Douglas J. Leith and Carl E. Rasmussen",
	title = "Derivative observations in {G}aussian Process models of dynamic systems",
	booktitle = "Advances in Neural Information Processing Systems",
	year = {2003}
}

@InCollection{ rifai2011higher,
	title = "Higher order contractive auto-encoder",
	author = "Salah Rifai and Gr{\'e}goire Mesnil and Pascal Vincent and Xavier Muller and Yoshua Bengio and Yann Dauphin and Xavier Glorot",
	booktitle = "Machine Learning and Knowledge Discovery in Databases",
	pages = "645--660",
	year = "2011",
	publisher = "Springer"
}

@InProceedings{ rifai2011contractive,
	title = "Contractive auto-encoders: Explicit invariance during feature extraction",
	author = "Salah Rifai and Pascal Vincent and Xavier Muller and Xavier Glorot and Yoshua Bengio",
	booktitle = "Proceedings of the 28th International Conference on Machine Learning",
	pages = "833--840",
	year = "2011"
}

@InProceedings{ martens2010deep,
	title = "Deep learning via {H}essian-free optimization",
	author = "James Martens",
	booktitle = "Proceedings of the 27th International Conference on Machine Learning",
	pages = "735--742",
	year = "2010"
}

@Article{ rippel2013high,
	title = "High-Dimensional Probability Estimation with Deep Density Models",
	author = "Oren Rippel and Ryan P. Adams",
	journal = "arXiv preprint arXiv:1302.5125",
	year = "2013"
}

@Article{ pascanu2012understanding,
	title = "Understanding the exploding gradient problem",
	author = "Razvan Pascanu and Tomas Mikolov and Yoshua Bengio",
	journal = "arXiv preprint arXiv:1211.5063",
	year = "2012"
}

@InProceedings{ glorot2011deep,
	title = "Deep Sparse Rectifier Networks",
	author = "Xavier Glorot and Antoine Bordes and Yoshua Bengio",
	booktitle = "Proceedings of the 14th International Conference on Artificial Intelligence and Statistics. JMLR W\&CP Volume",
	volume = "15",
	pages = "315--323",
	year = "2011"
}

@InProceedings{ lee2007sparse,
	title = "Sparse deep belief net model for visual area V2",
	author = "Honglak Lee and Chaitanya Ekanadham and Andrew Ng",
	booktitle = "Advances in Neural Information Processing Systems",
	pages = "873--880",
	year = "2007"
}

@InProceedings{ lawrence2007hierarchical,
	title = "Hierarchical {G}aussian process latent variable models",
	author = "Neil D. Lawrence and Andrew J. Moore",
	booktitle = "Proceedings of the 24th International Conference on Machine learning",
	pages = "481--488",
	year = "2007"
}

@Article{ bengio1994learning,
	title = "Learning long-term dependencies with gradient descent is difficult",
	author = "Yoshua Bengio and Patrice Simard and Paolo Frasconi",
	journal = "Neural Networks, IEEE Transactions on",
	volume = "5",
	number = "2",
	pages = "157--166",
	year = "1994",
	publisher = "IEEE"
}

@InProceedings{ gens2013learning,
	title = "Learning the Structure of Sum-Product Networks",
	author = "Robert Gens and Pedro Domingos",
	booktitle = "Proceedings of the 30th International Conference on Machine learning",
	year = "2013"
}

@InProceedings{ saxe2011random,
	title = "On random weights and unsupervised feature learning",
	author = "Andrew Saxe and Pang W. Koh and Zhenghao Chen and Maneesh Bhand and Bipin Suresh and Andrew Y. Ng",
	booktitle = "Proceedings of the 28th International Conference on Machine Learning",
	pages = "1089--1096",
	year = "2011"
}

@InProceedings{ saxedynamics,
	title = "Dynamics of learning in deep linear neural networks",
	author = "Andrew M. Saxe and James L. McClelland and Surya Ganguli",
	year = "2013",
	booktitle = "NIPS Workshop on Deep Learning"
}

@Article{ hermans2012recurrent,
	title = "Recurrent kernel machines: Computing with infinite echo state networks",
	author = "Michiel Hermans and Benjamin Schrauwen",
	journal = "Neural Computation",
	volume = "24",
	number = "1",
	pages = "104--133",
	year = "2012",
	publisher = "MIT Press"
}

@Article{ maunsell1983connections,
	title = "The connections of the middle temporal visual area ({MT}) and their relationship to a cortical hierarchy in the macaque monkey",
	author = "John H. R. Maunsell and David C. van Essen",
	journal = "Journal of neuroscience",
	volume = "3",
	number = "12",
	pages = "2563--2586",
	year = "1983",
	publisher = "Soc Neuroscience"
}

@MastersThesis{ srivastava2013improving,
	title = "Improving neural networks with dropout",
	author = "Nitish Srivastava",
	year = "2013",
	school = "University of Toronto"
}

@InProceedings{ baldi2013understanding,
	title = "Understanding dropout",
	author = "Pierre Baldi and Peter J. Sadowski",
	booktitle = "Advances in Neural Information Processing Systems",
	pages = "2814--2822",
	year = "2013"
}

@InProceedings{ wang2013fast,
	title = "Fast dropout training",
	author = "Sida Wang and Christopher Manning",
	booktitle = "Proceedings of the 30th International Conference on Machine Learning",
	pages = "118--126",
	year = "2013"
}

@Article{ hinton2012improving,
	title = "Improving neural networks by preventing co-adaptation of feature detectors",
	author = "Geoffrey Hinton and Nitish Srivastava and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov",
	journal = "arXiv preprint arXiv:1207.0580",
	year = "2012"
}

\% GPSS-research references

@Article{ dyke1997avoid,
	title = "How to avoid bad statistics",
	author = "George Dyke",
	journal = "Field crops research",
	volume = "51",
	number = "3",
	pages = "165--187",
	year = "1997",
	publisher = "Elsevier"
}

@Article{ kronberger2013evolution,
	title = "Evolution of Covariance Functions for {G}aussian Process Regression using Genetic Programming",
	author = "Gabriel Kronberger and Michael Kommenda",
	journal = "arXiv preprint arXiv:1305.3794",
	year = "2013"
}

@Article{ lazaro2010sparse,
	title = "Sparse spectrum {G}aussian process regression",
	author = "Miguel L{\'a}zaro-Gredilla and Joaquin Qui{\~n}onero-Candela and Carl E. Rasmussen and An{\'i}bal R. Figueiras-Vidal",
	journal = "Journal of Machine Learning Research",
	volume = "99",
	pages = "1865--1881",
	year = "2010",
	publisher = "MIT Press"
}

@Article{ garnett2010sequential,
	title = "Sequential {B}ayesian prediction in the presence of changepoints and faults",
	author = "Roman Garnett and Michael A. Osborne and Steven Reece and Alex Rogers and Stephen J. Roberts",
	journal = "The Computer Journal",
	volume = "53",
	number = "9",
	pages = "1430--1446",
	year = "2010",
	publisher = "Br Computer Soc"
}

@InProceedings{ FoxDunson:NIPS2012,
	author = "Emily B. Fox and David B. Dunson",
	title = "Multiresolution {G}aussian Processes",
	booktitle = "Advances in Neural Information Processing Systems 25",
	year = "2013",
	publisher = "MIT Press"
}

@Book{ lind2006basic,
	title = "Basic statistics for business and economics",
	author = "Douglas A. Lind and William G. Marchal and Samuel Adam Wathen",
	year = "2006",
	publisher = "McGraw-Hill/Irwin Boston"
}

@Article{ buja1989linear,
	title = "Linear smoothers and additive models",
	author = "Andreas Buja and Trevor J. Hastie and Robert J. Tibshirani",
	journal = "The Annals of Statistics",
	pages = "453--510",
	year = "1989",
	publisher = "JSTOR"
}

@Article{ Gelman1996,
	author = "Andrew Gelman and Xiao-li Meng and Hal Stern",
	journal = "Statistica Sinica",
	pages = "733--807",
	title = "Posterior predictive assessment of model fitness via realized discrepancies",
	volume = "6",
	year = "1996"
}

@Electronic{Eureqa,
  author = "Michael Schmidt and Hod Lipson",
  title = "Eureqa [Software]",
  year = "accessed February 2013",
  url = "http://www.eureqa.com"
}

@Book{ box2013time,
	title = "Time series analysis: forecasting and control",
	author = "George E.P. Box and Gwilym M. Jenkins and Gregory C. Reinsel",
	year = "1970",
	publisher = {John Wiley \& Sons}
}

@Book{ bochner1959lectures,
	title = "Lectures on Fourier integrals",
	author = "Salomon Bochner",
	volume = "42",
	year = "1959",
	publisher = "Princeton University Press"
}

@Electronic{ TSDL,
	author = "Rob J. Hyndman",
	title = "Time Series Data Library",
	year = "accessed July 2013",
	url = "http://data.is/TSDLdemo"
}

@InCollection{ VikashScene13,
	title = "Approximate {B}ayesian Image Interpretation using Generative Probabilistic Graphics Programs",
	author = "Vikash K. Mansinghka and Tejas D. Kulkarni and Yura N. Perov and Joshua B. Tenenbaum",
	booktitle = "Advances in Neural Information Processing Systems 26",
	pages = "1520--1528",
	year = "2013"
}

@article{ganesalingam2013fully,
  title={A fully automatic problem solver with human-style output},
  author={Ganesalingam, M. and Timonthy W. Gowers},
  journal={arXiv preprint arXiv:1309.4501},
  year={2013}
}

@Book{ zhu2007stochastic,
	title = "A stochastic grammar of images",
	author = "Song Chun Zhu and David Mumford",
	volume = "2",
	number = "4",
	year = "2007",
	publisher = "Now Publishers Inc"
}

@MastersThesis{ klenske2012nonparametric,
	title = "Nonparametric System Identification and Control for Periodic Error Correction in Telescopes",
	author = "Edgar Klenske",
	school = "University of Stuttgart",
	year = "2012"
}

@Article{ lloydgefcom2012,
	author = "James Robert Lloyd",
	title = "{GEFCom2012} Hierarchical Load Forecasting: Gradient boosting machines and {G}aussian processes",
	journal = "International Journal of Forecasting",
	year = "2013"
}

@InProceedings{ goodman2008church,
	title = "Church: A language for generative models",
	author = "Noah D. Goodman and Vikash K. Mansinghka and Daniel M. Roy and K. Bonawitz and Joshua B. Tenenbaum",
	booktitle = "Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence",
	pages = "220--229",
	year = "2008"
}

@InProceedings{ bach2004multiple,
	title = "Multiple kernel learning, conic duality, and the {SMO} algorithm",
	author = "Francis R. Bach and Gert R.G. Lanckriet and Michael I. Jordan",
	booktitle = "Proceedings of the 21st International Conference on Machine learning",
	year = "2004"
}

@Article{ gelman2012philosophy,
	title = "Philosophy and the practice of {B}ayesian statistics",
	author = "Andrew Gelman and Cosma R. Shalizi",
	journal = "British Journal of Mathematical and Statistical Psychology",
	year = "2012",
	publisher = "Wiley Online Library"
}

@Electronic{ gelman2013philblogpost,
	author = "Andrew Gelman",
	title = "Why waste time philosophizing?",
	type = "Blog post",
	year = "2013",
	url = "http://andrewgelman.com/2013/02/11/why-waste-time-philosophizing/"
}

@InProceedings{ barbu2012video,
	author = "Barbu, Andrei and Bridge, Alexander and Burchill, Zachary and Coroian, Dan and Dickinson, Sven and Fidler, Sanja and Michaux, Aaron and Mussman, Sam and Narayanaswamy, Siddharth and Salvi, Dhaval and Lara Schmidt and Jiangnan Shangguan and Jeffrey M. Siskind and Jarrell Waggoner and Song Wang and Jinlian Wei and Yifan Yin and Zhiqi Zhang",
	title = "Video in sentences out",
	booktitle = "Conference on Uncertainty in Artificial Intelligence",
	year = "2012"
}

@InProceedings{ saatcci2010gaussian,
	title = "{G}aussian process change point models",
	author = "Yunus Saat\c{c}i and Ryan D. Turner and Carl E. Rasmussen",
	booktitle = "Proceedings of the 27th International Conference on Machine Learning",
	pages = "927--934",
	year = "2010"
}

\% BMC References
\% =========================================================

@Article{ seeger2008information,
	title = "Information consistency of nonparametric {G}aussian process methods",
	author = "M.W. Seeger and S.M. Kakade and D.P. Foster",
	journal = "Information Theory, IEEE Transactions on",
	volume = "54",
	number = "5",
	pages = "2376--2382",
	year = "2008",
	publisher = "IEEE"
}

@InCollection{ NIPS2008_0240,
	title = "The {G}aussian Process Density Sampler",
	author = "Ryan P. Adams and Iain Murray and David J. C. MacKay",
	booktitle = "Advances in Neural Information Processing Systems 21",
	pages = "9--16",
	year = "2009"
}

@Article{ jones2006fixed,
	title = "Fixed-width output analysis for {M}arkov chain {M}onte {C}arlo",
	author = "G.L. Jones and M. Haran and B.S. Caffo and R. Neath",
	journal = "Journal of the American Statistical Association",
	volume = "101",
	number = "476",
	pages = "1537--1547",
	issn = "0162-1459",
	year = "2006",
	publisher = "ASA"
}

@Article{ rasmussen2003bayesian,
	title = "{B}ayesian {M}onte {C}arlo",
	author = "Carl E. Rasmussen and Zoubin Ghahramani",
	journal = "Advances in Neural Information Processing Systems",
	pages = "505--512",
	issn = "1049-5258",
	year = "2003"
}

@Article{ o1991bayes,
	title = "{B}ayes-hermite quadrature",
	author = "A. O'Hagan",
	journal = "Journal of Statistical Planning and Inference",
	volume = "29",
	number = "3",
	pages = "245--260",
	issn = "0378-3758",
	year = "1991",
	publisher = "Elsevier"
}

@Article{ kennedy1998bayesian,
	title = "Bayesian quadrature with non-normal approximating functions",
	author = "M. Kennedy",
	journal = "Statistics and Computing",
	volume = "8",
	number = "4",
	pages = "365--375",
	year = "1998",
	publisher = "Springer"
}

@Article{ skilling2006nested,
	title = "Nested sampling for general {B}ayesian computation",
	author = "J. Skilling",
	journal = "Bayesian Analysis",
	volume = "1",
	number = "4",
	pages = "833--860",
	year = "2006"
}

@mastersthesis{ murray2007advances,
	title = "Advances in {M}arkov chain {M}onte {C}arlo methods",
	author = "Iain Murray",
	journal = "University College London",
	year = "2007"
}

@Article{ Qi_hessianbasedmarkov,
	author = "Yuan Qi and Thomas P. Minka",
	title = "{H}essian-based {M}arkov Chain {M}onte-carlo Algorithms",
	year = "2002"
}

\% Additive GP References
\% ==============================================================


@article{yeh1998modeling,
  title={Modeling of strength of high-performance concrete using artificial neural networks},
  author={I-Cheng Yeh},
  journal={Cement and Concrete research},
  volume={28},
  number={12},
  pages={1797--1808},
  year={1998},
  publisher={Elsevier}
}

@Book{ macdonald1998symmetric,
	title = "Symmetric functions and {H}all polynomials",
	author = "Ian G. Macdonald",
	isbn = "0198504500",
	year = "1998",
	publisher = "{O}xford {U}niversity Press, USA"
}

@Book{ stanley2001enumerative,
	title = "Enumerative combinatorics",
	author = "R.P. Stanley",
	isbn = "0521789877",
	year = "2001",
	publisher = "{C}ambridge {U}niversity Press"
}

@Book{ vapnik1998statistical,
	title = "Statistical learning theory",
	author = "Vladimir N. Vapnik",
	volume = "2",
	year = "1998",
	publisher = "Wiley New York"
}

@Book{ shawe2004kernel,
	title = "Kernel methods for pattern analysis",
	author = "J. Shawe-Taylor and N. Cristianini",
	isbn = "0521813972",
	year = "2004",
	publisher = "{C}ambridge {U}niversity Press"
}

@Article{ craven1978smoothing,
	title = "Smoothing noisy data with spline functions",
	author = "P. Craven and Grace Wahba",
	journal = "Numerische Mathematik",
	volume = "31",
	number = "4",
	pages = "377--403",
	issn = "0029-599X",
	year = "1978",
	publisher = "Springer"
}

@Article{ friedman1991multivariate,
	title = "Multivariate adaptive regression splines",
	author = "Jerome H. Friedman",
	journal = "The annals of statistics",
	volume = "19",
	number = "1",
	pages = "1--67",
	issn = "0090-5364",
	year = "1991",
	publisher = "JSTOR"
}

@Article{ lin2006component,
	title = "Component selection and smoothing in multivariate nonparametric regression",
	author = "Y. Lin and H.H. Zhang",
	journal = "The Annals of Statistics",
	volume = "34",
	number = "5",
	pages = "2272--2297",
	issn = "0090-5364",
	year = "2006",
	publisher = "Institute of Mathematical Statistics"
}

@InProceedings{ 5589113,
	author = "J. Hartikainen and S. Särkkä",
	booktitle = "2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) ",
	title = "{K}alman filtering and smoothing solutions to temporal {G}aussian process regression models",
	year = "2010",
	volume = "",
	number = "",
	pages = "379--384",
	doi = "10.1109/MLSP.2010.5589113",
	ISSN = "1551-2541"
}

@article{Bach_HKL,
  title={High-dimensional non-linear variable selection through hierarchical kernel learning},
  author={Francis R. Bach},
  journal={arXiv preprint arXiv:0909.0844},
  year={2009}
}

@Article{ reich2009variable,
	title = "Variable selection in {B}ayesian smoothing spline {ANOVA} models: Application to deterministic computer codes",
	author = "B.J. Reich and C.B. Storlie and H.D. Bondell",
	journal = "Technometrics",
	volume = "51",
	number = "2",
	pages = "110--120",
	issn = "0040-1706",
	year = "2009",
	publisher = "ASA"
}

@InProceedings{ minka2001expectation,
	title = "Expectation propagation for approximate {B}ayesian inference",
	author = "Thomas P. Minka",
	booktitle = "Uncertainty in Artificial Intelligence",
	volume = "17",
	pages = "362--369",
	year = "2001"
}

@Article{ nocedal1980updating,
	title = "Updating quasi-{N}ewton matrices with limited storage",
	author = "Jorge Nocedal",
	journal = "Mathematics of computation",
	volume = "35",
	number = "151",
	pages = "773--782",
	year = "1980"
}

@Article{ friedman1981projection,
	title = "Projection pursuit regression",
	author = "Jerome H. Friedman and W. Stuetzle",
	journal = "Journal of the American statistical Association",
	volume = "76",
	number = "376",
	pages = "817--823",
	year = "1981"
}

@Article{ nelder1972generalized,
	title = "Generalized linear models",
	author = "John Ashworth Nelder and Robert W.M. Wedderburn",
	journal = "Journal of the Royal Statistical Society. Series A (General)",
	volume = "135",
	number = "3",
	pages = "370--384",
	year = "1972"
}

\% Warped mixtures references

@Article{ ng2002spectral,
	title = "On spectral clustering: Analysis and an algorithm",
	author = "Andrew Y. Ng and Michael I. Jordan and Yair Weiss",
	journal = "Advances in Neural Information Processing Systems",
	volume = "2",
	pages = "849--856",
	year = "2002"
}

@Article{ baskerville2011spatial,
	title = "Spatial guilds in the {S}erengeti food web revealed by a {B}ayesian group model",
	author = "E.B. Baskerville and A.P. Dobson and T. Bedford and S. Allesina and T.M. Anderson and M. Pascual",
	journal = "PLoS computational biology",
	volume = "7",
	number = "12",
	pages = "e1002321",
	year = "2011",
	publisher = "Public Library of Science"
}

\% Optimization References
\% ===============================================

@Article{ lizotte2008practical,
	title = "Practical {B}ayesian optimization",
	author = "D.J. Lizotte",
	year = "2008",
	publisher = "University of Alberta"
}

@InProceedings{ osborne2009gaussian,
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	author = "Michael A. Osborne and Roman Garnett and Stephen J. Roberts",
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	year = "2009"
}

@Book{ russell1991right,
	title = "Do the right thing",
	author = "S. Russell and E. Wefald",
	year = "1991",
	publisher = "MIT Press"
}

\% Infinite BQ references

@Article{ griffiths2005infinite,
	title = "Infinite latent feature models and the Indian buffet process",
	author = "T. Griffiths and Zoubin Ghahramani",
	year = "2005",
	publisher = "Gatsby Unit"
}

@InProceedings{ doshi2009accelerated,
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	pages = "273--280",
	year = "2009",
	organization = "ACM"
}

@Article{ CowlesCarlin96,
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	journal = "Journal of the American Statistical Association",
	number = "434",
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}

@TechReport{ minka2000dqr,
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}

@InProceedings{ guestrin1,
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}

@InProceedings{ guestrin2,
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	pages = "588--599"
}

@Article{ MCUnsound,
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}

@Article{ BZHermiteQuadrature,
	author = "A. O'Hagan",
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	pages = "245--260",
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	volume = "29",
	year = "1991"
}

@InProceedings{ BZMonteCarlo,
	author = "Carl E. Rasmussen and Zoubin Ghahramani",
	title = "{B}ayesian {M}onte {C}arlo",
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	year = "2003"
}

@Article{ Sriperumbudur2010,
	author = {Bharath K. Sriperumbudur and Arthur Gretton and Kenji Fukumizu and Bernhard Sch{\"o}lkopf and Gert R.G. Lanckriet},
	title = "Hilbert Space Embeddings and Metrics on Probability Measures",
	journal = "J. Mach. Learn. Res.",
	volume = "99",
	month = "August",
	year = "2010",
	pages = "1517--1561",
	publisher = "MIT Press",
	address = "Cambridge, MA, USA"
}

@InProceedings{ Song2008,
	author = {Le Song and Xinhua Zhang and Alex Smola and Arthur Gretton and Bernhard Sch{\"o}lkopf},
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	year = "2008",
	pages = "992--999"
}

@InProceedings{ chen2010super,
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}

@InProceedings{ welling2009herding,
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}

@Article{ bach2012equivalence,
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	year = "2012"
}

@InProceedings{ miller2009variational,
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	year = "2009"
}

@Article{ green1995reversible,
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@Article{ wood2007particle,
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	publisher = "MIT; 1998"
}

@Article{ o1986bayesian,
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	number = "82",
	year = "1986"
}

@PhDThesis{ cook1993sequential,
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	author = "T. Cook"
}

@Article{ bretthorst198931p,
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	author = "G.L. Bretthorst and J.J. Kotyk and J.J.H. Ackerman",
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}

@Article{ bretthorst1990bayesian,
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}

@Article{ pfingsten2006bayesian,
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	pages = "353--364",
	year = "2006",
	publisher = "Springer"
}

@InProceedings{ engel2007bayesian,
	title = "{B}ayesian policy gradient algorithms",
	author = "M.G.Y. Engel",
	booktitle = "Advances in Neural Information Processing Systems 19",
	volume = "19",
	pages = "457",
	year = "2007",
	organization = "The MIT Press"
}

@Article{ lodhi2002text,
	title = "Text classification using string kernels",
	author = "H. Lodhi and C. Saunders and J. Shawe-Taylor and N. Cristianini and C. Watkins",
	journal = "Journal of Machine Learning Research",
	volume = "2",
	pages = "419--444",
	year = "2002",
	publisher = "JMLR. org"
}

@Article{ gartner2003survey,
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	author = {T. G{\"a}rtner},
	journal = "ACM SIGKDD Explorations Newsletter",
	volume = "5",
	number = "1",
	pages = "49--58",
	year = "2003",
	publisher = "ACM"
}

\% Topology bib

@inproceedings{ginsbourger2012argumentwise,
  title={Argumentwise invariant kernels for the approximation of invariant functions},
  author={Ginsbourger, David and Bay, Xavier and Roustant, Olivier and Carraro, Laurent},
  booktitle={Annales de la Facult{\'e} de Sciences de Toulouse},
  year={2012}
}

@inproceedings{sudanese1984,
  author = {Doug Lerner and Dan Asimov},
  title = {The {S}udanese {M}{\"o}bius Band},
  booktitle = {{SIGGRAPH} Electronic Theatre},
  year = {1984}
}

@online{sudanesepict,
 author  = "{Wikimedia Commons}",
 title   = "Stereographic projection of a {S}udanese {M}{\"o}bius band",
 year    = "2005",
 urlseen = "2014-22-03",
 url     = "http://commons.wikimedia.org/wiki/File:MobiusSnail2B.png"
}

@online{mlhipster,
 author  = "@ML\_Hipster",
 title   = "“…essentially, all models are wrong, but yours are stupid too.” – {G}.{E}.{P}. {B}ox in a less than magnanimous mood.",
 year    = "2013",
 urlseen = "2014-03-30",
 url     = "https://twitter.com/ML_Hipster/status/394577463990181888"
}


@article{mercer1909functions,
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  author={Mercer, James},
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  pages={415--446},
  year={1909},
  publisher={JSTOR}
}

@incollection{minh2006mercer,
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  year={2006},
  publisher={Springer}
}


@Book{ flanders1989,
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	year = "1989"
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@Book{ rasmussen38gaussian,
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}

@Article{ vincent2002manifold,
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}

@Article{ bengio2006non,
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}

@Article{ tresp2001mixtures,
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	year = "2001",
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}

@Article{ rasmussen2000infinite,
	title = "The infinite {G}aussian mixture model",
	author = "Carl E. Rasmussen",
	journal = "Advances in Neural Information Processing Systems",
	year = "2000"
}

@InProceedings{ lawrence2009non,
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	year = "2009"
}

@InProceedings{ wassermann2008simultaneous,
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	year = "2008"
}

@InProceedings{ geiger2009rank,
	title = "Rank priors for continuous non-linear dimensionality reduction",
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	booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
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	year = "2009",
	organization = "IEEE"
}

@Article{ tipping1999probabilistic,
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}

@Article{ tipping1999mixtures,
	title = "Mixtures of probabilistic principal component analyzers",
	author = "Tipping, Michael E. and Bishop, Christopher M.",
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	number = "2",
	pages = "443--482",
	year = "1999",
	publisher = "MIT Press"
}

@Article{ lawrence2004gaussian,
	publisher = "MIT",
	title = "{Gaussian} process latent variable models for visualisation of high dimensional data",
	author = "Neil D. Lawrence",
	journal = "Advances in Neural Information Processing Systems",
	pages = "329--336",
	year = "2004"
}

@Article{ nickisch2010gaussian,
	title = "{G}aussian mixture modeling with {Gaussian} process latent variable models",
	author = "Hannes Nickisch and Carl E. Rasmussen",
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	pages = "272--282",
	year = "2010",
	publisher = "Springer"
}

@Article{ titsias2010bayesian,
	title = "{B}ayesian {Gaussian} process latent variable model",
	author = "Michalis Titsias and Neil D. Lawrence",
	journal = "International Conference on Artificial Intelligence and Statistics",
	year = "2010"
}

@InProceedings{ souvenir2005manifold,
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	year = "2005",
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}

@InProceedings{ cao2006nonlinear,
	title = "Nonlinear manifold clustering by dimensionality",
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	year = "2006",
	organization = "IEEE"
}

@InProceedings{ elhamifar2011sparse,
	author = "Ehsan Elhamifar and Ren{\'e} Vidal",
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	booktitle = "Advances in Neural Information Processing Systems",
	year = "2011",
	pages = "55--63"
}

@Article{ ferguson1973bayesian,
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	year = "1973",
	publisher = "JSTOR"
}

@Article{ maceachern1998estimating,
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@Article{ chang2011libsvm,
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	number = "3",
	year = "2011",
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}

@InProceedings{ salzmann2008local,
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	author = "Mathieu Salzmann and Raquel Urtasun and Pascal Fua",
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	year = "2008"
}

@InProceedings{ wang2003kernel,
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	year = "2003",
	organization = "Springer"
}

@Article{ rasmussen2002infinite,
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	pages = "881--888",
	year = "2002",
	publisher = "MIT"
}

@Article{ quinonero2005unifying,
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	year = "2005"
}

@Article{ zhang2011quasi,
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	year = "2011"
}

@Article{ snelson2006sparse,
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	year = "2006"
}

@Article{ ghahramani2000variational,
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	year = "2000"
}

@Article{ rand1971objective,
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@Article{ sethuraman94,
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@Article{ huelsenbeck2007inference,
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@InProceedings{ xing2006,
	author = "Eric P. Xing and Kyung-Ah Sohn and Michael I. Jordan and Yee-Whye Teh",
	title = "{B}ayesian multi-population haplotype inference via a hierarchical {D}irichlet process mixture",
	booktitle = "Proceedings of the 23rd international conference on Machine learning",
	year = "2006",
	pages = "1049--1056"
}

@Article{ choi2011evaluation,
	title = "Evaluation of {B}ayesian spatiotemporal latent models in small area health data",
	author = "J. Choi and A.B. Lawson and B. Cai and M. Hossain and others",
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	volume = "22",
	number = "8",
	pages = "1008--1022",
	year = "2011",
	publisher = "Wiley Online Library"
}

@Article{ lartillot2004bayesian,
	title = "A {B}ayesian mixture model for across-site heterogeneities in the amino-acid replacement process",
	author = "N. Lartillot and H. Philippe",
	journal = "Molecular biology and evolution",
	volume = "21",
	number = "6",
	pages = "1095--1109",
	year = "2004",
	publisher = "SMBE"
}

@Article{ rasmussen2009modeling,
	title = "Modeling and visualizing uncertainty in gene expression clusters using {D}irichlet process mixtures",
	author = "Carl E. Rasmussen and Bernard J. {De la Cruz} and Zoubin Ghahramani and David L. Wild",
	journal = "Computational Biology and Bioinformatics, IEEE/ACM Transactions on",
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	number = "4",
	pages = "615--628",
	year = "2009",
	publisher = "IEEE"
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@InProceedings{ Lawrence06localdistance,
	author = "Neil D. Lawrence",
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	pages = "513--520"
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@Article{ neal2003density,
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	year = "2003",
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@Article{ teh2006hierarchical,
	title = "Hierarchical {D}irichlet processes",
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@Article{ umistfaces,
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@InProceedings{ poon2011sum,
	author = "Hoifung Poon and Pedro Domingos",
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	year = "2011",
	pages = "689--690",
	organization = "IEEE"
}

@InProceedings{ DuvLloGroetal13,
	title = "Structure Discovery in Nonparametric Regression through Compositional Kernel Search",
	author = "David Duvenaud and James Robert Lloyd and Roger B. Grosse and Joshua B. Tenenbaum and Zoubin Ghahramani",
	year = "2013",
	booktitle = "Proceedings of the 30th International Conference on Machine Learning"
}


@INPROCEEDINGS{LloDuvGroetal14,
  title         = "Automatic Construction and Natural-Language Description of Nonparametric Regression Models",
  author        = {Lloyd, James Robert and Duvenaud, David and Roger B. Grosse and Tenenbaum, Joshua B. and Ghahramani, Zoubin},
  booktitle     = "Association for the Advancement of Artificial Intelligence (AAAI)",
  year          = "2014"
}

@Article{ bengio2006curse,
	author = "Yoshua Bengio and Olivier Delalleau and Nicolas {Le Roux}",
	pages = "107--114",
	title = "The Curse of Highly Variable Functions for Local Kernel Machines",
	journal = "Advances in Neural Information Processing Systems",
	volume = "18",
	issn = "1049-5258",
	year = "2006"
}

@inproceedings{WilAda13,
  title={{G}aussian process kernels for pattern discovery and extrapolation},
  author={Wilson, Andrew G. and Adams, Ryan P.},
  booktitle={Proceedings of the 30th International Conference on Machine Learning},
  pages={1067--1075},
  year={2013}
}


@PhDThesis{ kondor2008group,
	title = "Group theoretical methods in machine learning",
	author = "Imre Risi Kondor",
	school = "Columbia University",
	year = "2008"
}

@Article{ salakhutdinov2008using,
	author = "Ruslan Salakhutdinov and Geoffrey Hinton",
	title = "Using Deep Belief Nets to Learn Covariance Kernels for {G}aussian Processes",
	journal = "Advances in Neural information processing systems",
	volume = "20",
	pages = "1249--1256",
	year = "2008",
	booktitle = "Advances in Neural Information Processing Systems"
}

@InProceedings{ duvenaud2011additive11,
	author = "David Duvenaud and Hannes Nickisch and Carl E. Rasmussen",
	booktitle = "Advances in Neural Information Processing Systems 24",
	cat = "gp",
	title = "Additive {G}aussian Processes",
	year = {2011},
	address = "Granada, Spain",
	pages = "226--234"
}

@inproceedings{snoek2012practical,
  title={Practical {B}ayesian Optimization of Machine Learning Algorithms},
  author={Snoek, Jasper and Larochelle, Hugo and Ryan P. Adams},
  booktitle={Advances in Neural Information Processing Systems 25},
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