Search Results for author:
Found 5 papers, 2 papers with code
The importance of being constrained: dealing with infeasible solutions in Differential Evolution and beyond
Here, we demonstrate that, at least in algorithms based on Differential Evolution, this choice induces notably different behaviours - in terms of performance, disruptiveness and population diversity.
To BAN or not to BAN: Bayesian Attention Networks for Reliable Hate Speech Detection
Our approach not only improves the classification performance of the state-of-the-art multilingual BERT model but the computed reliability scores also significantly reduce the workload in an inspection of ofending cases and reannotation campaigns.
Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders
Due to complex experimental settings, missing values are common in biomedical data.
Prediction Uncertainty Estimation for Hate Speech Classification
As a result of social network popularity, in recent years, hate speech phenomenon has significantly increased.
Generating Data using Monte Carlo Dropout
In many such cases, generators of synthetic data with the same statistical and predictive properties as the actual data allow efficient simulations and development of tools and applications.
