Dr José Miguel Hernández Lobato

Title:	Research Associate
Group:	Computational and Biological Learning
Division:	Information Engineering, computing, control & mathematics
E-mail:	jmh233@eng.cam.ac.uk
Post:	University of Cambridge, Department of Engineering, Trumpington Street, Cambridge CB2 1PZ
Telephone:	+44 1223 7 48512
Fax:	+44 1223 3 32662

General:

Since June 2011 I am a research associate (postdoc) in the Machine Learning Group in the Computational and Biological Learning Lab at the University of Cambridge. Previously I had a teaching assistant position at Universidad Autónoma de Madrid. This is a link to my old homepage.

Research Interests:

• Sparse Bayesian Methods.
• Gaussian Processes.
• Matrix factorization methods.
• Efficient methods for approximate Bayesian inference.
• Causality.

Publications:

Journals

• Semiparametric Bivariate Archimedean Copulas,
  Hernández-Lobato J. M. and Suárez A.
  Computational Statistics & Data Analysis. Volume 55, Issue 6, Pages 2038-2058, 2011. [pdf]
• Network-based Sparse Bayesian Classification,
  Hernández-Lobato J. M., Hernández-Lobato D. and Suárez A.
  Pattern Recognition, Volume 44, Issue 4, Pages 886-900, 2011. [pdf]
• Expectation Propagation for Microarray Data Classification.
  Hernández-Lobato D., Hernández-Lobato J. M. and Suárez A.
  Pattern Recognition Letters, Volume 31, Issue, 12, Pages 1618-1626, 2010. [pdf]
• Bayes Machines for Binary Classification,
  Hernández-Lobato D. and Hernández-Lobato J. M.
  Pattern Recognition Letters, Volume 29, Issue 10, Pages 1466-1473, 2008. [pdf]

Conferences

• Transfer Learning with Copulas,
  David López-Paz and Hernández-Lobato J. M.
  In NIPS 2011 Workshop on Copulas in Machine Learning, Granada, Spain, December 16, 2011. [pdf]
• Expectation Propagation for the Estimation of Conditional Bivariate Copulas,
  Hernández-Lobato J. M., David López-Paz and Ghahramani Z.
  In NIPS 2011 Workshop on Copulas in Machine Learning, Granada, Spain, December 16, 2011. [pdf]
• Robust Multi-Class Gaussian Process Classification,
  Hernández-Lobato D., Hernández-Lobato J. M. and Dupont P.
  In Anual Conference on Neural Information Processing Systems, NIPS 2011, Granada, Spain, December 12-15, 2011. [pdf]
• Gaussianity Measures for Detecting the Direction of Causal Time Series,
  Hernández-Lobato J. M., Morales-Mombiela P. and Suárez A.
  In International Joint Conference on Artificial Intelligence, Barcelona, Spain, IJCAI 2011, pp. 1318-1323. [pdf]
• Expectation Propagation for Bayesian Multi-task Feature Selection,
  Hernández-Lobato D., Hernández-Lobato J. M., Helleppute T. and Dupont P.
  In European Conference on Machine Learning, Barcelona, Spain, ECML PKDD 2010, Part I, LNAI 6321, pp. 522-537, 2010. [pdf]
• Hub Gene Selection Methods for the Reconstruction of Transcription Networks,
  Hernández-Lobato J. M. and Dijkstra T. M. H.
  In European Conference on Machine Learning, Barcelona, Spain, ECML PKDD 2010, Part I, LNAI 6321, pp. 506-521, 2010. [pdf]
• Modeling Dependence with Semiparametric Archimedean Copulas,
  Hernández-Lobato J. M. and Suárez A.
  In International Workshop on Advances in Machine Learning for Computational Finance, AMLCF 2009. [video]
• GARCH Processes with Non-parametric Innovations for Market Risk Estimation,
  Hernández-Lobato J. M., Hernández-Lobato D. and Suárez A.
  In International Conference on Artificial Neural Networks, Porto, Portugal, ICANN 2007, Part I, LNCS 4668, pp. 718-727, 2007. [pdf]
• Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach,
  Hernández-Lobato J. M., Dijkstra T. and Heskes T.
  In Annual Conference on Neural Information Processing Systems, NIPS 2007, Vancouver, British Columbia, Canada, December 3-6, 2007. [pdf]
  
• Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm,
  Hernández-Lobato D., Hernández-Lobato J. M., Ruiz-Torrubiano R. and Valle A.
  In 7th Intelligent Data Engineering and Automated Learning, Burgos, Spain, IDEAL 2006, LNCS 4224, pp. 322-329, 2006. [pdf]
• Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis,
  Hernández-Lobato J. M. and Suárez A.
  In International Conference on Artificial Neural Networks, Athens, Greece, ICANN 2006, Part II, LNCS 4132, pp. 691-700, 2006. [pdf]

Ph.D. Thesis and Master Thesis

• Ph.D. Thesis, Balancing Flexibility and Robustness in Machine Learning: Semi-parametric Methods and Sparse Linear Models, December 2010. [pdf]
• Master Project, Time Series Models for Measuring Market Risk, July 2007. [pdf]

© Cambridge University Engineering Dept
Automatically generated: 2 June, 2011