Alfredo Cuesta-Infante
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Modeling tabular data using conditional gan
L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni
arXiv preprint arXiv:1907.00503, 2019
ATM: A distributed, collaborative, scalable system for automated machine learning
T Swearingen, W Drevo, B Cyphers, A Cuesta-Infante, A Ross, ...
2017 IEEE International Conference on Big Data (Big Data), 151-162, 2017
glUCModel: A monitoring and modeling system for chronic diseases applied to diabetes
JI Hidalgo, E Maqueda, JL Risco-Martín, A Cuesta-Infante, JM Colmenar, ...
Journal of biomedical informatics 48, 183-192, 2014
SteganoGAN: High capacity image steganography with GANs
KA Zhang, A Cuesta-Infante, L Xu, K Veeramachaneni
arXiv preprint arXiv:1901.03892, 2019
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
JM Górriz, J Ramírez, A Ortíz, FJ Martínez-Murcia, F Segovia, J Suckling, ...
Neurocomputing 410, 237-270, 2020
Modeling glycemia in humans by means of Grammatical Evolution
JI Hidalgo, JM Colmenar, JL Risco-Martin, A Cuesta-Infante, E Maqueda, ...
Applied Soft Computing 20, 40-53, 2014
Bivariate empirical and n-variate archimedean copulas in estimation of distribution algorithms
A Cuesta-Infante, R Santana, JI Hidalgo, C Bielza, P Larrańaga
IEEE Congress on Evolutionary Computation, 1-8, 2010
Lightweight tracking-by-detection system for multiple pedestrian targets
B Lacabex, A Cuesta-Infante, AS Montemayor, JJ Pantrigo
Integrated computer-aided engineering 23 (3), 299-311, 2016
Learning representations for log data in cybersecurity
I Arnaldo, A Cuesta-Infante, A Arun, M Lam, C Bassias, ...
International Conference on Cyber Security Cryptography and Machine Learning …, 2017
Learning vine copula models for synthetic data generation
Y Sun, A Cuesta-Infante, K Veeramachaneni
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5049-5057, 2019
Convolutional neural networks for computer vision-based detection and recognition of dumpsters
I Ramirez, A Cuesta-Infante, JJ Pantrigo, AS Montemayor, JL Moreno, ...
Neural Computing and Applications, 1-9, 2018
Bayesian capsule networks for 3D human pose estimation from single 2D images
I Ramirez, A Cuesta-Infante, E Schiavi, JJ Pantrigo
Neurocomputing 379, 64-73, 2020
Sample, estimate, tune: Scaling bayesian auto-tuning of data science pipelines
A Anderson, S Dubois, A Cuesta-Infante, K Veeramachaneni
2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017
Steganogan: Pushing the limits of image steganography
KA Zhang, A Cuesta-Infante, K Veeramachaneni
arXiv preprint arXiv:1901.03892 2, 2019
Copula graphical models for wind resource estimation
K Veeramachaneni, A Cuesta-Infante, UM O'Reilly
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
A Geiger, D Liu, S Alnegheimish, A Cuesta-Infante, K Veeramachaneni
arXiv preprint arXiv:2009.07769, 2020
Computer-implemented data analysis methods and systems for wind energy assessments
T Feldman-Fitzthum, U O'reilly, A Cuesta-Infante, K Veermachaneni
US Patent App. 14/563,418, 2015
Real time evolvable hardware for optimal reconfiguration of cusp-like pulse shapers
J Lanchares, O Garnica, JL Risco-Martín, JI Hidalgo, JM Colmenar, ...
Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2014
Robust invisible video watermarking with attention
KA Zhang, L Xu, A Cuesta-Infante, K Veeramachaneni
arXiv preprint arXiv:1909.01285, 2019
Comparative study of meta-heuristic 3D floorplanning algorithms
A Cuesta-Infante, JM Colmenar, Z Bankovic, JL Risco-Martín, M Zapater, ...
Neurocomputing 150, 67-81, 2015
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