Minimax robust detection: Classic results and recent advances
This paper provides an overview of results and concepts in minimax robust hypothesis
testing for two and multiple hypotheses. It starts with an introduction to the subject …
testing for two and multiple hypotheses. It starts with an introduction to the subject …
Fast Robust Matrix Completion via Entry-Wise ℓ0-Norm Minimization
Matrix completion (MC) aims at recovering missing entries, given an incomplete matrix.
Existing algorithms for MC are mainly designed for noiseless or Gaussian noise scenarios …
Existing algorithms for MC are mainly designed for noiseless or Gaussian noise scenarios …
Robust matrix completion based on factorization and truncated-quadratic loss function
Robust matrix completion refers to recovering a low-rank matrix given a subset of the entries
corrupted by gross errors, and has various applications since many real-world signals can …
corrupted by gross errors, and has various applications since many real-world signals can …
Robust low-rank matrix recovery via hybrid ordinary-Welsch function
As a widely-used tool to resist outliers, the correntropy criterion or Welsch function has
recently been exploited for robust matrix recovery. However, it down-weighs all observations …
recently been exploited for robust matrix recovery. However, it down-weighs all observations …
Robust PCA via non-convex half-quadratic regularization
In this paper, we propose a new non-convex regularization term named half-quadratic
function to achieve robustness and sparseness for robust principal component analysis, and …
function to achieve robustness and sparseness for robust principal component analysis, and …
[HTML][HTML] Detection of medium-voltage electricity theft types based on robust regression and convolutional neural network
Z Yi, C Min, Z Yang, X Rong, G Chen, L Hua - International Journal of …, 2024 - Elsevier
Electricity theft detection is very important for the economic benefits of power companies and
the effectiveness of safe operation of power systems. At present, the traditional power theft …
the effectiveness of safe operation of power systems. At present, the traditional power theft …
Fast and robust rank-one matrix completion via maximum correntropy criterion and half-quadratic optimization
Matrix completion refers to seeking a low-rank matrix to match an incomplete matrix and fill
its missing entries, and is an important topic because many real-world data can be modeled …
its missing entries, and is an important topic because many real-world data can be modeled …
Robust Low-Rank Matrix Completion via a New Sparsity-Inducing Regularizer
This paper presents a novel loss function referred to as hybrid ordinary-Welsch (HOW) and a
new sparsity-inducing regularizer associated with HOW. We theoretically show that the …
new sparsity-inducing regularizer associated with HOW. We theoretically show that the …
Exact matrix completion via smooth matrix factorization
X Luo, Z Zhang, W Wang… - Journal of Electronic …, 2024 - spiedigitallibrary.org
Matrix completion (MC) has been successfully applied to many real-world applications, such
as recommender systems and image inpainting. Traditional MC methods mainly aim at …
as recommender systems and image inpainting. Traditional MC methods mainly aim at …
Robust matrix completion via Novel M-estimator Functions
As most existing M-estimators down-weigh clean observations which are not corrupted by
outliers when resisting gross errors, we put forward a framework to produce numerous new …
outliers when resisting gross errors, we put forward a framework to produce numerous new …