Results 31 to 40 of about 5,238,545 (299)
Privacy-Preserving Parametric Inference: A Case for Robust Statistics [PDF]
Journal of the American Statistical Association, 2019 Differential privacy is a cryptographically motivated approach to privacy that has become a very active field of research over the last decade in theoretical computer science and machine learning.
Marco Avella-Medina
semanticscholar +1 more source
Improving Electronic Sensor Reliability by Robust Outlier Screening
Sensors, 2013 Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount.
Federico Cuesta +1 more
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Transcriptomic pan‐cancer analysis using rank‐based Bayesian inference
Molecular Oncology, 2023 The analysis of whole genomes of pan‐cancer data sets provides a challenge for researchers, and we contribute to the literature concerning the identification of robust subgroups with clear biological interpretation.
Valeria Vitelli +6 more
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Remote Sensing, 2023 A robust multisensor navigation filter design for the entry phase of next-generation Mars entry, descent, and landing (EDL) is presented. The entry phase is the longest and most uncertain portion of a Mars landing sequence. Navigation performance at this
Natnael S. Zewge, Hyochoong Bang
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Statistical Procedures and Robust Statistics [PDF]
, 2002 It is argued that a main aim of statistics is to produce statistical procedures which in this article are defined as algorithms with inputs and outputs. The structure and properties of such procedures are investigated with special reference to topological and testing considerations.
openaire +4 more sources
Frontiers in Psychology, 2013 Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers.
Cyril R Pernet +2 more
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HOW TO REDUCE DIMENSIONALITY OF DATA: ROBUSTNESS POINT OF VIEW [PDF]
Serbian Journal of Management, 2015 Data analysis in management applications often requires to handle data with a large number of variables. Therefore, dimensionality reduction represents a common and important step in the analysis of multivariate data by methods of both statistics and ...
Jan Kalina, Dita Rensová
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Robust regularized singular value decomposition with application to mortality data [PDF]
, 2013 We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year.
Huang, Jianhua Z. +2 more
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HIGHLY ROBUST METHODS IN DATA MINING [PDF]
Serbian Journal of Management, 2013 This paper is devoted to highly robust methods for information extraction from data, with a special attention paid to methods suitable for management applications.
Jan Kalina
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Robust Dynamic Mode Decomposition
IEEE Access, 2022 This paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy ...
Amir Hossein Abolmasoumi +2 more
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