Robustness against outliers is a desirable property of any unsupervised learning scheme. In particular, probability density estimators benefit from incorporating this feature. A possible strategy to achieve this goal is to substitute the sample mean and the sample covariance matrix by more robust location and spread estimators. Here we use the L1-median to develop a nonparametric probability density function (PDF) estimator. We prove its most relevant properties, and we show its performance in density estimation and classification applications.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1142/S0129065709002075 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Association between neutrophil to high-density lipoprotein ratio and no-reflow after coronary intervention: A cross-sectional study.
Medicine (Baltimore)
January 2025
Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan, China.
Inflammatory responses and lipid metabolism disorders are key components in the development of coronary artery disease and contribute to no-reflow after coronary intervention. This study aimed to investigate the association between the neutrophil to high-density lipoprotein ratio (NHR) and no-reflow phenomenon in ST-segment elevation myocardial infarction (STEMI) patients after primary percutaneous coronary intervention (PPCI). This study enrolled 288 patients with STEMI from September 1st, 2022 to February 29th, 2024, in the Zhengzhou Central Hospital Affiliated to Zhengzhou University.
View Article and Find Full Text PDFGenerative adversarial local density-based unsupervised anomaly detection.
PLoS One
January 2025
School of Information Science and Engineering, Xinjiang University, Urumqi, China.
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly detection methods overlook the importance of local density, limiting their effectiveness in detecting anomaly objects in complex data distributions. To address this challenge, we introduce a generative adversarial local density-based anomaly detection (GALD) method, which combines the data distribution modeling capabilities of GANs with local synthetic density analysis.
View Article and Find Full Text PDFThe Group-Algebraic Formalism of Quantum Probability and Its Applications in Quantum Statistical Mechanics.
Entropy (Basel)
January 2025
Department of Physics and Fujian Provincial Key Laboratory of Low Dimensional Condensed Matter Physics, Xiamen University, Xiamen 361005, China.
We show that the theory of quantum statistical mechanics is a special model in the framework of the quantum probability theory developed by mathematicians, by extending the characteristic function in the classical probability theory to the quantum probability theory. As dynamical variables of a quantum system must respect certain commutation relations, we take the group generated by a Lie algebra constructed with these commutation relations as the bridge, so that the classical characteristic function defined in a Euclidean space is transformed to a normalized, non-negative definite function defined in this group. Indeed, on the quantum side, this group-theoretical characteristic function is equivalent to the density matrix; hence, it can be adopted to represent the state of a quantum ensemble.
View Article and Find Full Text PDFAnalysis of Risk Factors Associated with Organic Erectile Dysfunction in Patients with Type 2 Diabetes Mellitus and Erectile Dysfunction.
Discov Med
January 2025
Department of Urology, The Affiliated Hefei Hospital of Anhui Medical University (The Second People's Hospital of Hefei), 230011 Hefei, Anhui, China.
Background: Diabetes mellitus is a common metabolic disorder, and diabetic erectile dysfunction (DMED) is one of its common complications. The differentiation of the types of erectile dysfunction (ED) is fundamental to treatment, yet there is a lack of simple and efficacious tools for this purpose in clinical practice. In this study, we endeavor to predict ED types using commonly available clinical data from diabetic patients, aiming to develop and assess a risk prediction model for organic erectile dysfunction in individuals with type 2 diabetes.
View Article and Find Full Text PDFIncreased nerve density adversely affects outcome in colorectal cancer and denervation suppresses tumor growth.
J Transl Med
January 2025
Department of Oncology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200092, P.R. China.
Background: The colon and rectum are highly innervated, with neural components within the tumor microenvironment playing a significant role in colorectal cancer (CRC) progression. While perineural invasion (PNI) is associated with poor prognosis in CRC, the impact of nerve density and diameter on tumor behavior remains unclear. This study aims to evaluate the prognostic value of nerve characteristics in CRC and to verify the impact of nerves on tumor growth.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!