Antonio D'Ambrosio

Orcid: 0000-0002-1905-037X

According to our database1, Antonio D'Ambrosio authored at least 17 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
Clustering directional data through depth functions.
Comput. Stat., September, 2023

2021
Depth-based classification of directional data.
Expert Syst. Appl., 2021

Adjusted Concordance Index: an Extensionl of the Adjusted Rand Index to Fuzzy Partitions.
J. Classif., 2021

2020
Fuzzy logic aggregation of crisp data partitions as learning analytics in triage decisions.
Expert Syst. Appl., 2020

Robust mean-variance portfolio through the weighted L<sup>p</sup> depth function.
Ann. Oper. Res., 2020

2019
Informative trees by visual pruning.
Expert Syst. Appl., 2019

Median constrained bucket order rank aggregation.
Comput. Stat., 2019

2018
A P-spline based clustering approach for portfolio selection.
Expert Syst. Appl., 2018

2017
Regression trees for multivalued numerical response variables.
Expert Syst. Appl., 2017

A differential evolution algorithm for finding the median ranking under the Kemeny axiomatic approach.
Comput. Oper. Res., 2017

Analysis of Web Visit Histories, Part II: Predicting Navigation by Nested STUMP Regression Trees.
J. Classif., 2017

2016
Parsimonious time series clustering using P-splines.
Expert Syst. Appl., 2016

Accurate algorithms for identifying the median ranking when dealing with weak and partial rankings under the Kemeny axiomatic approach.
Eur. J. Oper. Res., 2016

Analysis of Web Visit Histories, Part I: Distance-Based Visualization of Sequence Rules.
J. Classif., 2016

2013
Clustering and Prediction of Rankings Within a Kemeny Distance Framework.
Proceedings of the Algorithms from and for Nature and Life, 2013

2012
Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm.
J. Classif., 2012

2007
Robust Tree-Based Incremental Imputation Method for Data Fusion.
Proceedings of the Advances in Intelligent Data Analysis VII, 2007


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