Luis Rademacher

University of California, Davis

H-index: 15

North America-United States

About Luis Rademacher

Luis Rademacher, With an exceptional h-index of 15 and a recent h-index of 9 (since 2020), a distinguished researcher at University of California, Davis, specializes in the field of algorithms, geometry, randomness, machine learning, computational learning theory.

His recent articles reflect a diverse array of research interests and contributions to the field:

On the Nyström Approximation for Preconditioning in Kernel Machines

Euclidean distance compression via deep random features

Expansion of random 0/1 polytopes

Improved Bounds for the Expected Number of k-Sets

Estranged facets and -facets of Gaussian random point sets

The smoothed complexity of Frank–Wolfe methods via conditioning of random matrices and polytopes

Algebraic k-Sets and Generally Neighborly Embeddings

Overcomplete order-3 tensor decomposition, blind deconvolution, and Gaussian mixture models

Luis Rademacher Information

University	University of California, Davis
Position	Department of Mathematics
Citations(all)	1194
Citations(since 2020)	487
Cited By	948
hIndex(all)	15
hIndex(since 2020)	9
i10Index(all)	16
i10Index(since 2020)	9
Email	Access Email
University Profile Page	University of California, Davis
Google Scholar	View Google Scholar Profile

Luis Rademacher Skills & Research Interests

algorithms

geometry

randomness

machine learning

computational learning theory

Top articles of Luis Rademacher

Title	Journal	Author(s)	Publication Date
On the Nyström Approximation for Preconditioning in Kernel Machines		Amirhesam Abedsoltan Parthe Pandit Luis Rademacher Mikhail Belkin	2024/4/18
Euclidean distance compression via deep random features	arXiv preprint arXiv:2403.01327	Brett Leroux Luis Rademacher	2024/3/2
Expansion of random 0/1 polytopes	Random Structures & Algorithms	Brett Leroux Luis Rademacher	2024/3
Improved Bounds for the Expected Number of k-Sets	Discrete & Computational Geometry	Brett Leroux Luis Rademacher	2023/10
Estranged facets and -facets of Gaussian random point sets	arXiv preprint arXiv:2307.00687	Brett Leroux Luis Rademacher	2023/7/2
The smoothed complexity of Frank–Wolfe methods via conditioning of random matrices and polytopes	Mathematical Statistics and Learning	Luis Rademacher Chang Shu	2022/12/21
Algebraic k-Sets and Generally Neighborly Embeddings	Discrete & Computational Geometry	Brett Leroux Luis Rademacher	2022/3/1
Overcomplete order-3 tensor decomposition, blind deconvolution, and Gaussian mixture models	SIAM Journal on Mathematics of Data Science	Haolin Chen Luis Rademacher	2022
Efficiency of the floating body as a robust measure of dispersion		Joseph Anderson Luis Rademacher	2020