Current Position September 2016 - present. University Lecturer in Machine Learning (equivalent to US Assistant Professor) at the Department of Engineering in the University of Cambridge, UK. Past Positions September 2014 - August 2016. Postdoctoral fellow in the Harvard Intelligent Probabilistic Systems group, School of Engineering and Applied Sciences, Harvard University, working with Prof. Ryan Adams…
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Jose Miguel Hernandez Lobato
Camino ●●●●●●●rete 37
Mora●●●●rzal , Madrid, 28411
ES
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Jose Miguel Hernandez Lobato
Camino ●●●●●●●rete 37
Mora●●●●rzal , Madrid, 28411
ES
View this contact
Jose Miguel Hernandez Lobato
Camino ●●●●●●●rete 37
Mora●●●●rzal , Madrid, 28411
ES
View this contact
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José Miguel Hernández-Lobato | jmhl.org Reviews
https://jmhl.org
Current Position September 2016 - present. University Lecturer in Machine Learning (equivalent to US Assistant Professor) at the Department of Engineering in the University of Cambridge, UK. Past Positions September 2014 - August 2016. Postdoctoral fellow in the Harvard Intelligent Probabilistic Systems group, School of Engineering and Applied Sciences, Harvard University, working with Prof. Ryan Adams…
jmhl.org
Publications | José Miguel Hernández-Lobato
https://jmhl.org/publications
Depeweg S., Hernández-Lobato J. M., Doshi-Velez F. and Udluft S. Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks. ArXiv:1605.07127, 2016. [pdf]. Hernández Lobato J. M., Gelbart M. A., Adams R. P, Hoffman M. W. and Ghahramani Z. A General Framework for Constrained Bayesian Optimization using Information-based Search. Journal of Machine Learning Research, (in press), 2016. [pdf]. Hernández-Lobato J. M., Hernández-Lobato D. and Suárez A. Shastri L., Gharamani Z&#...
Talks and Posters | José Miguel Hernández-Lobato
https://jmhl.org/talks
Bayesian Optimization of Genetic Programs. Foundry Annual Meeting. Broad Institute of MIT and Harvard, Cambridge, MA, USA. Black-Box Alpha Divergence Minimization. International Conference on Machine Learning, New York City, USA. [slides]. Bayesian Machine Learning for Efficient Optimization of Black-box Functions. University of Toronto, Toronto, Canada. Bayesian Machine Learning for Efficient Optimization of Black-box Functions. Edinburgh University, Edinburgh, UK. EPFL, Lausanne, Switzerland. Machine L...
Teaching | José Miguel Hernández-Lobato
https://jmhl.org/teaching
Bayesian Optimization (lectures), Universidad Autónoma de Madrid, Spain. Teaching assistant for CS281 (Advanced Machine Learning), School of Engineering and Applied Sciences, Harvard University. 4th-year project supervisions, Engineering Department, Cambridge University. Bayesian Inference (Lectures). Charles University in Prague, Czech Republic. 4th-year project supervisions, Engineering Department, Cambridge University. Computer Programming II (Practicals). Universidad Autónoma de Madrid, Spain.
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People | Harvard Intelligent Probabilistic Systems
http://hips.seas.harvard.edu/content/people
Harvard Intelligent Probabilistic Systems. School of Engineering and Applied Sciences. Harvard School of Engineering and Applied Sciences. Ryan P. Adams.
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José Miguel Hernández-Lobato
September 2016 – present. University Lecturer in Machine Learning (equivalent to US Assistant Professor. At the Department of Engineering in the University of Cambridge. September 2014 – August 2016. Postdoctoral fellow in the Harvard Intelligent Probabilistic Systems. Group, School of Engineering and Applied Sciences, Harvard University. Working with Prof. Ryan Adams. On Bayesian optimization and other machine learning problems. June 2011 – August 2014. Department of Engineering, University of Cambridge.
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