Ferenc Huszár

Ferenc Huszar

Ferenc Huszár
PhD student in machine learning

Computational and Biological Learning LabDepartment of Engineering, University of Cambridge
Trinity College Cambridge
Trumpington Street, Cambridge CB2 1PZ, UK
tel: +44 (0) 1223 748 511e-mail: fh277@cam.ac.ukroom number BE4-40

About me

I am a second year PhD student in the Machine Learning Group. My supervisor is Carl Edward Rasmussen, and my advisor is Zoubin Ghahramani. I am interested in the mathematics and statistical theory underlying machine learning algorithms, in particular Bayesian nonparametrics and reproducing kernel Hilbert spaces. Before starting my PhD I also worked on computational cognitive science in Máté Lengyel’s Computational Learning and Memory Group. More recently I have gained interest in quantum information and statistics.

For a graphical representation of my research interests click here.



In preparation

figure 1
Huszár F and Houlsby NMT.Adaptive Bayesian Quantum Tomographysubmitted for review[ arXiv ]

Huszár F and Lacoste-Julien S.

A kernel approach to tractable Bayesian Nonparametrics.

[ arXiv ]

Houlsby NMT, Huszár F, Ghahramani Z, Lengyel M.

Bayesian active learning by disagreement (BALD).

under review

Peer-reviewed conference papers

Lacoste-Julien S, Huszár F, Ghahramani Z.

Approximate inference for the loss-calibrated Bayesian.

Proceedings of the 14th International Conference on Artificial Intelligence and Statistics, JMLR W&CP 15:416-424, 2011

[ pdf | supplementary ]

Huszár F, Noppeney U, Lengyel M.

Mind reading by machine learning: A doubly Bayesian method for inferring mental representations.

Proceedings of the 32nd Annual Conference of the Cognitive Science Society, 2810-2815, 2010.

[ pdf | supplementary ]

Book chapter

Szathmáry E, Szatmáry Z, Ittzes P, Számadó S, Zachar I, Huszár F, Fedor A, Varga M.

In silico evolutionary developmental neurobiology and the origin of natural language.

In (C. Lyon, C. et al. eds) Emergence of Communication and Language, 151-188. 2007.

.pdf | www ]

Technical reports, etc

Huszár F, O’Keeffe SG, Hein J.

Corner cutting approaches to Ethier-Griffiths-Tavaré recursions.

Technical report, Genome Analysis and Bioinformatics Group, Department of Statistics, University of Oxford, 2008.

pdf | www ]