Alan Turing Institute,
96 Euston Road, NW1 2DB,
E-mail: htyagi (at) turing (dot) ac (dot) uk
Interests: Approximation theory, Online optimization, Learning
theory, Compressed sensing, Low dimensional models for high
Bio: I am a
Research fellow at the Alan Turing Institute (ATI), and also
affiliated to the School of Mathematics, University of Edinburgh. I
completed my PhD at the Institute of Theoretical Computer Science,
ETH Zurich. Earlier, I obtained a MSc degree in Communication
Systems from EPFL, and a Bachelors degree in Electrical and
Electronics Engineering from NIT Surathkal, Karnataka, India.
Workshop on Approximating High Dimensional Functions on 18, 19 December at the Alan Turing Institute
Sebastian Stich and Bernd Gärtner, On
two continuum armed bandit problems in high dimensions, Theory
of Computing Systems (TOCS), 2016, 58:1, 191-222.
Anastasios Kyrillidis, Bernd Gärtner and Andreas Krause,
Algorithms for Learning
Sparse Additive Models with Interactions in High Dimensions,
Information and Inference (to appear), 2017.
low dimensional models for functions in high dimensions, ETH
sampling analysis for quadratic embeddings of Riemannian manifolds,
Master Thesis in Communication Systems, EPFL, July 2011.
ridge functions in high dimensions via low rank matrix recovery.
April 23, 2012, Mittagsseminar,
estimation for smooth embeddings of manifolds. January 15, 2013,
armed bandit problem of few variables in high dimensions. July 16,
sampling for learning SPAMs in high dimensions. October 28, 2014,
estimation for smooth embeddings of manifolds. August, 2015,
Information and Inference best paper prize meeting, University of
Sparse Additive Models with Interactions in High Dimensions
May 11, 2016,
19th International Conference on Artificial Intelligence and
Statistics (AISTATS), Cadiz, Spain
2016, ANC Seminar, School of Informatics, University of Edinburgh,
2016, ACM Seminar, School of Mathematics, University of Edinburgh,
2017, Algorithms Day, Alan Turing Institute, London, UK
2017, Numerical Analysis Seminar, University of Oxford, UK
on "Learning functions from data" at the 27th Biennial
Numerical Analysis Conference at Glasgow, 27