activity
20172021
most citedSparse recovery based on q-ratio constrained minimal singular values

1 citations · 1 across the 5 of their papers we have counts for

collaborators

15 papers

math.ST2021

A note on sharp oracle bounds for Slope and Lasso

Zhiyong Zhou

In this paper, we study the sharp oracle bounds for Slope and Lasso and generalize the results in Bellec et al. (2018) to allow the case that the parameter vector is not exactly sp…

stat.ML2021

A Unified Framework for Constructing Nonconvex Regularizations

Zhiyong Zhou

Over the past decades, many individual nonconvex methods have been proposed to achieve better sparse recovery performance in various scenarios. However, how to construct a valid no…

math.NA2021

Sparse recovery based on the generalized error function

Zhiyong Zhou

In this paper, we propose a novel sparse recovery method based on the generalized error function. The penalty function introduced involves both the shape and the scale parameters,…

cs.IT2021

Block sparse signal recovery via minimizing the block -ratio sparsity

Zhiyong Zhou

In this paper, we propose a method for block sparse signal recovery that minimizes the block -ratio sparsity $\left(\lVert z\rVert_{2,1}/\lVert z\rVert_{2,q}\right)^{\frac{q}{q-…

cs.IT2020

Minimization of the -ratio sparsity with for signal recovery

Zhiyong Zhou, Jun Yu

In this paper, we propose a general scale invariant approach for sparse signal recovery via the minimization of the -ratio sparsity. When , both the theoretic…

eess.SP2019

Statistical inference for block sparsity of complex signals

Jianfeng Wang, Zhiyong Zhou, Jun Yu

Block sparsity is an important parameter in many algorithms to successfully recover block sparse signals under the framework of compressive sensing. However, it is often unknown an…