Results 231 to 240 of about 544,201 (272)

Outlier-Robust Learning with Continuously Differentiable Least Trimmed Squares

Pattern Recognition
Lei Xing, Yufei Liu, Linhai Xu, Badong Chen   +3 more
openaire   +2 more sources

Sparse least trimmed squares regression with compositional covariates for high-dimensional data

Bioinform., 2021
MOTIVATION High-throughput sequencing technologies generate a huge amount of data, permitting the quantification of microbiome compositions. The obtained data are essentially sparse compositional data vectors, namely vectors of bacterial gene proportions
G. Monti, P. Filzmoser
semanticscholar   +1 more source

Identification of Near‐Infrared Characteristic Bands of Small Intestine Necrosis Based on Least Trimmed Squares With Regularization

Journal of Biophotonics
Hyperspectral imaging is a promising tool for identifying ischemic necrotic small intestine. To analyze the causes of small bowel necrosis, studying characteristic bands is crucial.
Jingzhi Li, Chenxi Peng, Yuxuan Hou, Guangzao Huang, Lechao Zhang, Xiaojing Chen, Zhonghao Xie, Shujat Ali, Libin Zhu, Xiaoqing Chen   +9 more
semanticscholar   +1 more source

Outlier Handling in Applied Regression: Performance Comparison Between Least Trimmed Squares and Maximum Likelihood-Type Estimators

Jurnal ilmu komputer dan aplikasi
Poverty analysis often relies on regression models whose performance can deteriorate in the presence of outliers, leading to biased estimates and unreliable conclusions.
U. Negeri, Cinta Rizki Oktarina, Andini Setyo Anggraeni, Muhammad Arib Alwansyah, Reza Pahlepi   +4 more
semanticscholar   +1 more source

Non-asymptotic analysis of the performance of the penalized least trimmed squares in sparse models

arXiv.org
The least trimmed squares (LTS) estimator is a renowned robust alternative to the classic least squares estimator and is popular in location, regression, machine learning, and AI literature.
Yijun Zuo
semanticscholar   +1 more source

Robust Panel Data Regression Analysis using the Least Trimmed Squares (LTS) Estimator on Poverty Line Data in Lampung Province

Integra: Journal of Integrated Mathematics and Computer Science
Robust regression is an alternative method in regression analysis designed to produce stable parameter estimates, even when the data contain outliers or deviate from classical assumptions.
Windi Lestari, Widiarti, B. H. S. Utami, Mustofa Usman, Vitri Aprilla Handayani   +4 more
semanticscholar   +1 more source

Study on least trimmed squares fuzzy neural networks

2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering, 2010
In this paper, least trimmed squares (LTS) estimators, frequently used in robust (or resistant) linear parametric regression problems, will be generalized to nonparametric LTS-fuzzy neural networks (LTS-FNNs) for nonlinear regression problems. Emphasis is put particularly on the robustness against outliers.
Hsu-Kun Wu, Jer-Guang Hsieh, Ker-Wei Yu
openaire   +1 more source

Trimmed diffusion least mean squares for distributed estimation

2015 IEEE International Conference on Digital Signal Processing (DSP), 2015
We consider the problem of distributed estimation, where a set of nodes is required to collectively estimate network parameters from noisy measurements. The problem is important when modeling a wide class of real-time sensor networks, where efficiency, robustness, and low power consumption are desired features. In this work, we focus on diffusion-based
Hong Ji, Xiaohan Yang, Badong Chen
openaire   +1 more source

Least Tail-Trimmed Squares for Infinite Variance Autoregressions

SSRN Electronic Journal, 2012
We develop a robust least squares estimator for autoregressions with possibly heavy tailed errors. Robustness to heavy tails is ensured by negligibly trimming the squared error according to extreme values of the error and regressors. Tail‐trimming ensures asymptotic normality and super‐‐convergence with a rate comparable to the highest achieved amongst
openaire   +2 more sources

Parameters Estimation for Short Line Using the Least Trimmed Squares (LTS)

IEEE PES Innovative Smart Grid Technologies Conference, 2019
This paper introduces a novel method to estimate positive and zero-sequence transmission line parameters for short line. The current and voltage measurements are taken from synchronized phasor measurements (PMUs) located at both terminals of the line ...
Ahmed Momen, B. Johnson, Y. Chakhchoukh
semanticscholar   +1 more source