Teaser: Fast and certifiable point cloud registration
We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …
The ABC of DC programming
W de Oliveira - Set-Valued and Variational Analysis, 2020 - Springer
A function is called DC if it is expressible as the difference of two convex functions. In this
work, we present a short tutorial on difference-of-convex optimization surveying and …
work, we present a short tutorial on difference-of-convex optimization surveying and …
Simultaneous feature selection and outlier detection with optimality guarantees
Biomedical research is increasingly data rich, with studies comprising ever growing
numbers of features. The larger a study, the higher the likelihood that a substantial portion of …
numbers of features. The larger a study, the higher the likelihood that a substantial portion of …
[PDF][PDF] LinRegOutliers: A Julia package for detecting outliers in linear regression
LinRegOutliers is a Julia package that implements a number of outlier detection algorithms
for linear regression. The package also implements robust covariance matrix estimation and …
for linear regression. The package also implements robust covariance matrix estimation and …
Learning distributed channel access policies for networked estimation: data-driven optimization in the mean-field regime
M Vasconcelos - Learning for Dynamics and Control …, 2022 - proceedings.mlr.press
The problem of communicating sensor measurements over shared networks is prevalent in
many modern large-scale distributed systems such as cyber-physical systems, wireless …
many modern large-scale distributed systems such as cyber-physical systems, wireless …
Comparison of Outlier Detection Methods in Linear Regression: A Multiple-Criteria Decision-Making Approach
MH Satman - Acta Infologica, 2023 - dergipark.org.tr
This paper focuses on the application of a suite of simulation studies to assess wellknown
and contemporary outlier detection methods in linear regression. These simulations vary …
and contemporary outlier detection methods in linear regression. These simulations vary …
Approaches for Outlier Detection in Sparse High-Dimensional Regression Models
L Insolia - 2022 - ricerca.sns.it
Modern regression studies often encompass a very large number of potential predictors,
possibly larger than the sample size, and sometimes growing with the sample size itself …
possibly larger than the sample size, and sometimes growing with the sample size itself …
Solution methodologies for minimizing a sum of pointwise minima of two functions
X Zuo, Y Jiang - Optimization Letters, 2023 - Springer
In this paper, an NP-hard problem of minimizing a sum of pointwise minima of two functions
is considered. Using a new equivalent formula, we propose a smooth approximation and an …
is considered. Using a new equivalent formula, we propose a smooth approximation and an …
Vysvětlitelnost neuronových sítí
D Vojtěch - 2023 - dspace.cvut.cz
Často diskutovaným problémem ve strojovém učení je vysvětlitelnost neuronových sítí.
Neuronové sítě zaznamenaly v posledních letech masivní rozvoj–používají se v široké škále …
Neuronové sítě zaznamenaly v posledních letech masivní rozvoj–používají se v široké škále …