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Juan S. Angarita-Zapata
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2020 – today
- 2023
- [c5]Ryan Dave, Juan S. Angarita-Zapata
, Isaac Triguero
:
Hyper-Stacked: Scalable and Distributed Approach to AutoML for Big Data. CD-MAKE 2023: 82-102 - [c4]Arka Ghosh, Juan S. Angarita-Zapata, Antonio D. Masegosa, Ander Arriandiaga Laresgoiti:
A Taxonomy of Signal Vehicle Coupled Control from a Mathematical Programming Perspective. ITSC 2023: 5597-5602 - [i1]Juan S. Angarita-Zapata, Antonio D. Masegosa, Isaac Triguero
:
AutoEn: An AutoML method based on ensembles of predefined Machine Learning pipelines for supervised Traffic Forecasting. CoRR abs/2303.10732 (2023) - 2021
- [j3]Juan S. Angarita-Zapata
, Ainhoa Alonso-Vicario
, Antonio D. Masegosa
, Jon Legarda
:
A Taxonomy of Food Supply Chain Problems from a Computational Intelligence Perspective. Sensors 21(20): 6910 (2021) - [j2]Juan S. Angarita-Zapata
, Gina Paola Maestre-Gongora
, Jenny Fajardo Calderín
:
A Bibliometric Analysis and Benchmark of Machine Learning and AutoML in Crash Severity Prediction: The Case Study of Three Colombian Cities. Sensors 21(24): 8401 (2021) - 2020
- [c3]Juan S. Angarita-Zapata
, Antonio D. Masegosa
, Isaac Triguero
:
General-Purpose Automated Machine Learning for Transportation: A Case Study of Auto-sklearn for Traffic Forecasting. IPMU (2) 2020: 728-744
2010 – 2019
- 2019
- [j1]Juan S. Angarita-Zapata
, Antonio D. Masegosa
, Isaac Triguero
:
A Taxonomy of Traffic Forecasting Regression Problems From a Supervised Learning Perspective. IEEE Access 7: 68185-68205 (2019) - [c2]Antonio D. Masegosa, Eneko Osaba
, Juan S. Angarita-Zapata
, Ibai Laña
, Javier Del Ser
:
Nature-inspired metaheuristics for optimizing information dissemination in vehicular networks. GECCO (Companion) 2019: 1312-1320 - 2018
- [c1]Juan S. Angarita-Zapata
, Isaac Triguero
, Antonio D. Masegosa
:
A Preliminary Study on Automatic Algorithm Selection for Short-Term Traffic Forecasting. IDC 2018: 204-214
Coauthor Index
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