Zobrazeno 1 - 10
of 2 902
pro vyhledávání: '"Soares, Carlos"'
Financial fraud is the cause of multi-billion dollar losses annually. Traditionally, fraud detection systems rely on rules due to their transparency and interpretability, key features in domains where decisions need to be explained. However, rule sys
Externí odkaz:
http://arxiv.org/abs/2408.12989
Autor:
Gomes, Inês, Teixeira, Luís F., van Rijn, Jan N., Soares, Carlos, Restivo, André, Cunha, Luís, Santos, Moisés
The increasing use of deep learning across various domains highlights the importance of understanding the decision-making processes of these black-box models. Recent research focusing on the decision boundaries of deep classifiers, relies on generate
Externí odkaz:
http://arxiv.org/abs/2408.06302
We introduce the Robustness of Hierarchically Organized Time Series (RHiOTS) framework, designed to assess the robustness of hierarchical time series forecasting models and algorithms on real-world datasets. Hierarchical time series, where lower-leve
Externí odkaz:
http://arxiv.org/abs/2408.03399
Accurate evaluation of forecasting models is essential for ensuring reliable predictions. Current practices for evaluating and comparing forecasting models focus on summarising performance into a single score, using metrics such as SMAPE. We hypothes
Externí odkaz:
http://arxiv.org/abs/2406.16590
The effectiveness of univariate forecasting models is often hampered by conditions that cause them stress. A model is considered to be under stress if it shows a negative behaviour, such as higher-than-usual errors or increased uncertainty. Understan
Externí odkaz:
http://arxiv.org/abs/2406.17008
Most forecasting methods use recent past observations (lags) to model the future values of univariate time series. Selecting an adequate number of lags is important for training accurate forecasting models. Several approaches and heuristics have been
Externí odkaz:
http://arxiv.org/abs/2405.11237
Autor:
Dutra, Milena O., Soares, Carlos E. S., Ferreira, Bárbara C. F., Ribeiro, Christiano W. R., Scussel, Vildes M.
Publikováno v:
Julius-Kühn-Archiv, Vol 463, Iss 2, Pp 1116-1126 (2018)
The storage conditions are of extreme importance with regards to grains (cereal & pulses) components (carbohydrates, lipids, proteins) preservation and quality for industry (that may interfere to whole process and quality of the final product). In ad
Externí odkaz:
https://doaj.org/article/caf70f540cc04a6aaacbf4a9085eef40
Autor:
Martins, Camila S., Soares, Carlos E. da S., Maria, Giovana de S., Taiane Klaumann, Milena de O. D., Ribeiro, Cristiano W.R., Ferreira, Bárbara C.F., Scussel, Vildes M.
Publikováno v:
Julius-Kühn-Archiv, Vol 463, Iss 1, Pp 60-65 (2018)
Oats (Avena sativa L.) have reached the healthy food market worldwide due to its special nutrients composition and fiber high quality. Therefore, quality & safety control is a must, both during the storage and commercialization stages. The current st
Externí odkaz:
https://doaj.org/article/aa819eb323d64ae5bf9fe115167803f9
Recent state-of-the-art forecasting methods are trained on collections of time series. These methods, often referred to as global models, can capture common patterns in different time series to improve their generalization performance. However, they
Externí odkaz:
http://arxiv.org/abs/2404.18537
Forecasting methods are affected by data quality issues in two ways: 1. they are hard to predict, and 2. they may affect the model negatively when it is updated with new data. The latter issue is usually addressed by pre-processing the data to remove
Externí odkaz:
http://arxiv.org/abs/2404.18273