Luis Rademacher

Orcid: 0000-0001-8708-2755

According to our database1, Luis Rademacher authored at least 34 papers between 2004 and 2023.

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Bibliography

2023
Improved Bounds for the Expected Number of k-Sets.
Discret. Comput. Geom., October, 2023

On the Nystrom Approximation for Preconditioning in Kernel Machines.
CoRR, 2023

2022
Overcomplete Order-3 Tensor Decomposition, Blind Deconvolution, and Gaussian Mixture Models.
SIAM J. Math. Data Sci., 2022

Algebraic k-Sets and Generally Neighborly Embeddings.
Discret. Comput. Geom., 2022

2020
The Minimum Euclidean-Norm Point in a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential.
SIAM J. Comput., 2020

The smoothed complexity of Frank-Wolfe methods via conditioning of random matrices and polytopes.
CoRR, 2020

Efficiency of the floating body as a robust measure of dispersion.
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

2018
Eigenvectors of Orthogonally Decomposable Functions.
SIAM J. Comput., 2018

2017
Heavy-Tailed Analogues of the Covariance Matrix for ICA.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
On packing and covering polyhedra in infinite dimensions.
Oper. Res. Lett., 2016

Basis Learning as an Algorithmic Primitive.
Proceedings of the 29th Conference on Learning Theory, 2016

The Hidden Convexity of Spectral Clustering.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Query Complexity of Sampling and Small Geometric Partitions.
Comb. Probab. Comput., 2015

Optimal Recovery in Noisy ICA.
CoRR, 2015

A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Heavy-Tailed Independent Component Analysis.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014
Lower Bounds for the Average and Smoothed Number of Pareto-Optima.
Theory Comput., 2014

Expanders via Random Spanning Trees.
SIAM J. Comput., 2014

Learning a Hidden Basis Through Imperfect Measurements: An Algorithmic Primitive.
CoRR, 2014

The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Blind Signal Separation in the Presence of Gaussian Noise.
Proceedings of the COLT 2013, 2013

Efficient Learning of Simplices.
Proceedings of the COLT 2013, 2013

2012
Efficient learning of simplices
CoRR, 2012

Lower Bounds for the Average and Smoothed Number of Pareto Optima.
Proceedings of the IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 2012

2010
Efficient Volume Sampling for Row/Column Subset Selection.
Proceedings of the 51th Annual IEEE Symposium on Foundations of Computer Science, 2010

2009
Optimization of a convex program with a polynomial perturbation.
Oper. Res. Lett., 2009

Expanders via random spanning trees.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

Learning Convex Bodies is Hard.
Proceedings of the COLT 2009, 2009

2007
Approximating the centroid is hard.
Proceedings of the 23rd ACM Symposium on Computational Geometry, 2007

2006
Matrix Approximation and Projective Clustering via Volume Sampling.
Theory Comput., 2006

Dispersion of Mass and the Complexity of Randomized Geometric Algorithms.
Electron. Colloquium Comput. Complex., 2006

Computing Equilibrium Prices in Exchange Economies with Tax Distortions.
Proceedings of the Automata, Languages and Programming, 33rd International Colloquium, 2006

2004
Testing Geometric Convexity.
Proceedings of the FSTTCS 2004: Foundations of Software Technology and Theoretical Computer Science, 2004


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