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1,014 results on '"Lopez, Julio"'

1. A survey on cutting-edge relation extraction techniques based on language models

Author

Diaz-Garcia, Jose A. and Lopez, Julio Amador Diaz

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

This comprehensive survey delves into the latest advancements in Relation Extraction (RE), a pivotal task in natural language processing essential for applications across biomedical, financial, and legal sectors. This study highlights the evolution and current state of RE techniques by analyzing 137 papers presented at the Association for Computational Linguistics (ACL) conferences over the past four years, focusing on models that leverage language models. Our findings underscore the dominance of BERT-based methods in achieving state-of-the-art results for RE while also noting the promising capabilities of emerging large language models (LLMs) like T5, especially in few-shot relation extraction scenarios where they excel in identifying previously unseen relations., Comment: 50 pages, under review in Artificial Intelligence Review

Published
2024

2. OWAdapt: An adaptive loss function for deep learning using OWA operators

Author

Maldonado, Sebastián, Vairetti, Carla, Jara, Katherine, Carrasco, Miguel, and López, Julio

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we propose a fuzzy adaptive loss function for enhancing deep learning performance in classification tasks. Specifically, we redefine the cross-entropy loss to effectively address class-level noise conditions, including the challenging problem of class imbalance. Our approach introduces aggregation operators, leveraging the power of fuzzy logic to improve classification accuracy. The rationale behind our proposed method lies in the iterative up-weighting of class-level components within the loss function, focusing on those with larger errors. To achieve this, we employ the ordered weighted average (OWA) operator and combine it with an adaptive scheme for gradient-based learning. Through extensive experimentation, our method outperforms other commonly used loss functions, such as the standard cross-entropy or focal loss, across various binary and multiclass classification tasks. Furthermore, we explore the influence of hyperparameters associated with the OWA operators and present a default configuration that performs well across different experimental settings., Comment: 15 pages, 1 figure, published

Published
2023
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3. Convective boundary layer sensible and latent heat flux lidar observations and towards new model parametrizations

Author

Gibert, Fabien, Edouart, Dimitri, Monnier, Paul, Collignan, Julie, Lopez, Julio, and Cénac, Claire

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

Model parametrizations in the convective boundary layer are still at work especially in the interfacial layers with the surface and the free troposphere. The present paper reports simultaneous turbulence-scale lidar observations of wind speed, temperature and specific humidity in the convective boundary layer in temperate and semi-arid regions. The collected data are used to assess new parametrizations in particular in the entrainment layer.

Published
2022

20. Improved Outcomes with Heavy Silicone Oil in Complex Primary Retinal Detachment: A Large Multicenter Matched Cohort Study

Author

Ellabban, Abdallah A., Chandra, Aman, Davies, Andrew, Morris, Andrew H.C., Meireles, Angelina, Casswell, Anthony G., Jalil, Assad, Babar, Atiq, Groenewald, Carl, Goldsmith, Craig, Laidlaw, David Alistair H., Steel, David H., Yorston, David, Vayalambrone, Deepak, Sanchez-Chicharro, Diego, Hughes, Edward H., Herbert, Edward N., Uys, Enslin, Jenkins, Huw, Pearce, Ian A., Masri, Ibrahim, Khan, Imran, Mitrut, Izabela, Paget, James, Park, Jonathan, Smith, Jonathan, Gonzalez-Lopez, Julio J., Balaggan, Kamaljit Sinbgh, Cornish, Kurt Spiteri, Wakely, Laura, Membrey, Luke, Figueroa, Marta S., Crama, Niels, Chua, Paul Y., Sheard, Richard, Hillier, Roxane, Cherubini, Sandro Di Simplicio, Tan, Shi Z., Tarafdar, Sonali, Winder, Stephen, Cochrane, Timothy, Williamson, Tom H., Ivanova, Tsveta, Papastavrou, Vasileios T., Tanner, Vaughan, Forsaa, Vegard, Le Mer, Yannick, and Tzoumas, Nikolaos

Published
2024
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23. Correcting public opinion trends through Bayesian data assimilation

Author

Hendrickx, Robin, Arcucci, Rossella, Lopez, Julio Amador Dıaz, Guo, Yi-Ke, and Kennedy, Mark

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Measuring public opinion is a key focus during democratic elections, enabling candidates to gauge their popularity and alter their campaign strategies accordingly. Traditional survey polling remains the most popular estimation technique, despite its cost and time intensity, measurement errors, lack of real-time capabilities and lagged representation of public opinion. In recent years, Twitter opinion mining has attempted to combat these issues. Despite achieving promising results, it experiences its own set of shortcomings such as an unrepresentative sample population and a lack of long term stability. This paper aims to merge data from both these techniques using Bayesian data assimilation to arrive at a more accurate estimate of true public opinion for the Brexit referendum. This paper demonstrates the effectiveness of the proposed approach using Twitter opinion data and survey data from trusted pollsters. Firstly, the possible existence of a time gap of 16 days between the two data sets is identified. This gap is subsequently incorporated into a proposed assimilation architecture. This method was found to adequately incorporate information from both sources and measure a strong upward trend in Leave support leading up to the Brexit referendum. The proposed technique provides useful estimates of true opinion, which is essential to future opinion measurement and forecasting research.

Published
2021

24. A methodology to evaluate corroded RC structures using a probabilistic damage approach

Author

Coelho, Karolinne O., Leonel, Edson D., and Flórez-López, Julio

Subjects
Mathematics - Numerical Analysis
Abstract

Several aspects influence corrosive processes in RC structures, such as environmental conditions, structural geometry, and mechanical properties. Since these aspects present large randomnesses, probabilistic models allow a more accurate description of the corrosive phenomena. On the other hand, the definition of limit states, applied in the reliability assessment, requires a proper mechanical model. In this context, this study proposes an accurate methodology for the mechanical-probabilistic modelling of RC structures subjected to reinforcements' corrosion. To this purpose, an improved damage approach is proposed to define the limit states for the probabilistic modelling, considering three main degradation phenomena: concrete cracking, rebar yielding, and rebar corrosion caused either by chlorides or carbonation process. The stochastic analysis is evaluated by the Monte Carlo simulation method due to the computational efficiency of the LDMC. The proposed mechanical-probabilistic methodology is implemented in a computational framework and applied to the analysis of a simply supported RC beam, and a 2D RC frame. Curves illustrate the probability of failure over a service life of 50 years. Moreover, the proposed model allows drawing the probability of failure map and then identify the critical failure path for progressive collapse analysis. Collapse path changes caused by the corrosion phenomena are observed.

Published
2021

27. Convective Boundary Layer Sensible and Latent Heat Flux Lidar Observations and Towards New Model Parametrisations

Author

Gibert, Fabien, Edouart, Dimitri, Monnier, Paul, Collignan, Julie, Lopez, Julio, Cénac, Claire, Sullivan, John T., editor, Leblanc, Thierry, editor, Tucker, Sara, editor, Demoz, Belay, editor, Eloranta, Edwin, editor, Hostetler, Chris, editor, Ishii, Shoken, editor, Mona, Lucia, editor, Moshary, Fred, editor, Papayannis, Alexandros, editor, and Rupavatharam, Krishna, editor

Published
2023
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28. All Trolls Have One Mission: An Entropy Analysis of Political Misinformation Spreaders

Author

Diaz-Garcia, J. Angel, López, Julio Amador Díaz, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Larsen, Henrik Legind, editor, Martin-Bautista, Maria J., editor, Ruiz, M. Dolores, editor, Andreasen, Troels, editor, Bordogna, Gloria, editor, and De Tré, Guy, editor

Published
2023
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31. The Humira in Ocular Inflammations Taper (HOT) Study

Author

Pichi, Francesco, Smith, Scott D., Goldstein, Debra A., Baddar, Dina, Gerges, Terese K.A., Janetos, Timothy M., Ruiz-Cruz, Matilde, Elena Concha-del-Río, Luz, Maruyama, Kazuichi, Carina ten Berge, Josianne, Rombach, Saskia M., Cimino, Luca, Bolletta, Elena, Miserocchi, Elisabetta, Scandale, Pierluigi, Serafino, Massimiliano, Camicione, Paola, Androudi, Sofia, Gonzalez-Lopez, Julio J., Lim, Lyndell L., Singh, Nandini, Gupta, Vishali, Gupta, Nikita, Amer, Radgonde, Dodds, Emilio M., Inchauspe, Sebastian, Munk, Marion R., Donicova, Emilia, Carreño, Ester, Takeuchi, Masaru, Chee, Soon-Phaik, Chew, Milton C., Agarwal, Aniruddha, Schlaen, Ariel, Gómez, Ramiro A., Couto, Cristobal A., Khairallah, Moncef, and Neri, Piergiorgio

Published
2024
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40. The Detection, Extraction, and Classification of Human Pose in Alzheimer's Patients

Author

Castillo Salazar, David R., Lanzarini, Laura, Gómez Alvarado, Héctor Fernando, Cabrera López, Julio Rafael, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Troiano, Luigi, editor, Vaccaro, Alfredo, editor, Kesswani, Nishtha, editor, Díaz Rodriguez, Irene, editor, and Brigui, Imene, editor

Published
2022
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