Miriam Esteve

About Miriam Esteve

Miriam Esteve, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Universidad Miguel Hernández de Elche, specializes in the field of Quantum Computing, Applied and Computational Mathematics, Data Mining, Big Data, Artificial Intelligence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Trajectory Classification through Topological Data Analysis Perspectives

Estimating production functions through additive models based on regression splines

Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques

How to peel a data envelopment analysis frontier: A cross-validation-based approach

An unsupervised learning-based generalization of Data Envelopment Analysis

TOPIC 10.1 CONJUNCTIVE ANALYSIS OF CASE CONFIGURATIONS

Measuring dynamic inefficiency through machine learning techniques

Gradient tree boosting and the estimation of production frontiers

Miriam Esteve Information

University

Position

Center of Operations Research (CIO). (UMH) 03202 Elche

Citations(all)

188

Citations(since 2020)

185

Cited By

35

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

6

i10Index(since 2020)

6

Email

University Profile Page

Universidad Miguel Hernández de Elche

Google Scholar

View Google Scholar Profile

Miriam Esteve Skills & Research Interests

Quantum Computing

Applied and Computational Mathematics

Data Mining

Big Data

Artificial Intelligence

Top articles of Miriam Esteve

Title

Journal

Author(s)

Publication Date

Trajectory Classification through Topological Data Analysis Perspectives

Miriam Esteve

Antonio Falcó

2024/3/8

Estimating production functions through additive models based on regression splines

European Journal of Operational Research

Victor J España

Juan Aparicio

Xavier Barber

Miriam Esteve

2024/1/16

Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques

Mathematics

Raul Moragues

Juan Aparicio

Miriam Esteve

2023/6/5

How to peel a data envelopment analysis frontier: A cross-validation-based approach

Journal of the Operational Research Society

Juan Aparicio

Miriam Esteve

2023/12/2

An unsupervised learning-based generalization of Data Envelopment Analysis

Operations Research Perspectives

Raul Moragues

Juan Aparicio

Miriam Esteve

2023/12/1

TOPIC 10.1 CONJUNCTIVE ANALYSIS OF CASE CONFIGURATIONS

Understanding Crime and Place: A Methods Handbook

Timothy C Hart

Asier Moneva

Miriam Esteve

2023/3/24

Measuring dynamic inefficiency through machine learning techniques

Expert Systems with Applications

Juan Aparicio

Miriam Esteve

Magdalena Kapelko

2023/10/15

Gradient tree boosting and the estimation of production frontiers

Expert Systems with Applications

Maria D Guillen

Juan Aparicio

Miriam Esteve

2023/3/15

Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study

Operational Research

Raul Moragues

Juan Aparicio

Miriam Esteve

2023/9

Performance Evaluation of Decision-Making Units Through Boosting Methods in the Context of Free Disposal Hull: Some Exact and Heuristic Algorithms

International Journal of Information Technology & Decision Making

Maria D Guillen

Juan Aparicio

Miriam Esteve

2023/1/31

Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull

European Journal of Operational Research

Miriam Esteve

Juan Aparicio

Jesus J Rodriguez-Sala

Joe Zhu

2023/1/16

Disseminating fear in 140 characters: a pilot study in Twitter following the Barcelona terror attacks

Contextual and Crosslinguistic Facets of Emotion Concepts

Tobias Gretenkort

Francisco Javier Castro-Toledo

Miriam Esteve

Fernando Miró-Llinares

2023/7/12

eat: An R Package for fitting Efficiency Analysis Trees.

R J.

Miriam Esteve

Victor España

Juan Aparicio

Xavier Barber

2022/12

The estimation of productive efficiency through machine learning techniques: Efficiency analysis trees

Juan Aparicio

Miriam Esteve

Jesus J Rodriguez-Sala

Jose L Zofio

2021/12/17

Conjunctive analysis of case configurations (CACC)

Timothy C Hart

Asier Moneva

Miriam Esteve

2021

The Effects of Abrupt Changing Data in CART Inference Models

Miriam Esteve

Nuria Mollá-Campello

Jesús J Rodríguez-Sala

Alejandro Rabasa

2021

Heuristic and Backtracking Algorithms for Improving the Performance of Efficiency Analysis Trees

IEEE Access

Miriam Esteve

Jesús Javier Rodríguez-Sala

José Juan López-Espín

Juan Aparicio

2021/1/25

Efficiency analysis trees: A new methodology for estimating production frontiers through decision trees

Expert Systems with Applications

Miriam Esteve

Juan Aparicio

Alejandro Rabasa

Jesus J Rodriguez-Sala

2020/12/30

“Fear in 280 characters”: A new approach for evaluation of fear over time in cyberspace 1

Francisco J Castro-Toledo

Tobias Gretenkort

Miriam Esteve

Fernando Miró-Llinares

2020/7/15

CACC: Conjunctive Analysis of Case Configurations

CrimRxiv

Miriam Esteve

Asier Moneva

Timothy Hart

2020/4/27

See List of Professors in Miriam Esteve University(Universidad Miguel Hernández de Elche)

Co-Authors

H-index: 32
Juan Aparicio

Juan Aparicio

Universidad Miguel Hernández de Elche

H-index: 22
Jose Juan López Espín

Jose Juan López Espín

Universidad Miguel Hernández de Elche

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