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Found 12 papers, 7 papers with code
Time Series Data Augmentation as an Imbalanced Learning Problem
We use these techniques to create synthetic time series observations and improve the accuracy of forecasting models.
Conformalized Selective Regression
However, this focus neglects the significant influence of model-specific biases on a model's performance.
Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective
The yield of a chemical reaction quantifies the percentage of the target product formed in relation to the reactants consumed during the chemical reaction.
Experiential-Informed Data Reconstruction for Fishery Sustainability and Policies in the Azores
Fishery analysis is critical in maintaining the long-term sustainability of species and the livelihoods of millions of people who depend on fishing for food and income.
A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics
In light of claims that predictive performance and fairness can be jointly optimized, we find this is only possible at the expense of data privacy.
Class-Imbalanced Learning on Graphs: A Survey
Concerning the latter, we critically analyze recent work in CILG and discuss urgent lines of inquiry within the topic.
Robustness Evaluation of Regression Tasks with Skewed Domain Preferences
In natural phenomena, data distributions often deviate from normality.
Differentially-Private Data Synthetisation for Efficient Re-Identification Risk Control
We also show how our method improves time requirements by at least a factor of 9 and is a resource-efficient solution that ensures high performance without specialised hardware.
Model Optimization in Imbalanced Regression
In this paper, our goal is to study the impacts of using SERA as an optimization criterion in imbalanced regression tasks.
Towards a Data Privacy-Predictive Performance Trade-off
In this paper, we aim to evaluate the existence of a trade-off between data privacy and predictive performance in classification tasks.
VEST: Automatic Feature Engineering for Forecasting
Time series forecasting is a challenging task with applications in a wide range of domains.
Real-time 2019 Portuguese Parliament Election Results Dataset
This paper presents a data set describing the evolution of results in the Portuguese Parliamentary Elections of October 6$^{th}$ 2019.
