Sjoerd Dirksen | DeepAI

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∙ 07/24/2023

Tuning-free one-bit covariance estimation using data-driven dithering

We consider covariance estimation of any subgaussian distribution from f...

0 Sjoerd Dirksen, et al. ∙

∙ 01/11/2023

Plug-in Channel Estimation with Dithered Quantized Signals in Spatially Non-Stationary Massive MIMO Systems

As the array dimension of massive MIMO systems increases to unprecedente...

0 Tianyu Yang, et al. ∙

∙ 04/08/2022

Fast metric embedding into the Hamming cube

We consider the problem of embedding a subset of ℝ^n into a low-dimensio...

0 Sjoerd Dirksen, et al. ∙

∙ 01/13/2022

Sharp estimates on random hyperplane tessellations

We study the problem of generating a hyperplane tessellation of an arbit...

0 Sjoerd Dirksen, et al. ∙

∙ 07/31/2021

The Separation Capacity of Random Neural Networks

Neural networks with random weights appear in a variety of machine learn...

0 Sjoerd Dirksen, et al. ∙

∙ 06/11/2021

New challenges in covariance estimation: multiple structures and coarse quantization

In this self-contained chapter, we revisit a fundamental problem of mult...

0 Johannes Maly, et al. ∙

∙ 04/02/2021

Covariance estimation under one-bit quantization

We consider the classical problem of estimating the covariance matrix of...

0 Sjoerd Dirksen, et al. ∙

∙ 09/17/2020

Binarized Johnson-Lindenstrauss embeddings

We consider the problem of encoding a set of vectors into a minimal numb...

0 Sjoerd Dirksen, et al. ∙

∙ 07/08/2020

Statistical post-processing of wind speed forecasts using convolutional neural networks

Current statistical post-processing methods for probabilistic weather fo...

0 Simon Veldkamp, et al. ∙

∙ 05/14/2020

Sparse recovery in bounded Riesz systems with applications to numerical methods for PDEs

We study sparse recovery with structured random measurement matrices hav...

0 Simone Brugiapaglia, et al. ∙

∙ 12/17/2018

Robust one-bit compressed sensing with partial circulant matrices

We present optimal sample complexity estimates for one-bit compressed se...

0 Sjoerd Dirksen, et al. ∙

∙ 05/23/2018

Robust one-bit compressed sensing with non-Gaussian measurements

We study memoryless one-bit compressed sensing with non-Gaussian measure...

0 Sjoerd Dirksen, et al. ∙

∙ 02/17/2014

Dimensionality reduction with subgaussian matrices: a unified theory

We present a theory for Euclidean dimensionality reduction with subgauss...

0 Sjoerd Dirksen, et al. ∙

∙ 11/11/2013

Toward a unified theory of sparse dimensionality reduction in Euclidean space

Let Φ∈R^m× n be a sparse Johnson-Lindenstrauss transform [KN14] with s n...

0 Jean Bourgain, et al. ∙

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