Hemant Tyagi (2012) ‒ LIONS ‐ EPFL

Internship project topic:

Low dimensional models for high dimensional data.

Biography

Hemant received a master degree in Communication Systems from EPFL in 2011 with a thesis titles “Local sampling analysis for quadratic embeddings of Riemmanian manifold”. He is currently pursuing a PhD in Prof. Emo Welzs’s research group. His research interestes are approximation theory, online optimization, computational learning theory and low dimensional models for high dimensional data.

Publications (most recent)

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Sparse non-negative super-resolution – simplified and stabilised

A. Eftekhari; J. Tanner; A. Thompson; B. Toader; H. Tyagi

Applied And Computational Harmonic Analysis. 2021-01-01. Vol. 50, p. 216-280. DOI : 10.1016/j.acha.2019.08.004.

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Learning non-parametric basis independent models from point queries via low-rank methods

H. Tyagi; V. Cevher

Applied And Computational Harmonic Analysis. 2014. Vol. 37, num. 3, p. 389-412. DOI : 10.1016/j.acha.2014.01.002.

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Tangent Space Estimation Bounds for Smooth Manifolds

H. Tyagi; E. Vural; P. Frossard

2013. SAMPTA, July, 2013.

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Tangent space estimation for smooth embeddings of Riemannian manifolds

H. Tyagi; E. Vural; P. Frossard

Information and Inference: A Journal of the IMA. 2013. Vol. 2, num. 1, p. 69-114. DOI : 10.1093/imaiai/iat003.

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Learning Ridge Functions With Randomized Sampling In High Dimensions

H. Tyagi; V. Cevher

2012. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, March 25-39, 2012. p. 2025-2028. DOI : 10.1109/ICASSP.2012.6288306.

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