Users can note which content they would like to view more frequently. Instagram is handing users some control in deciding what content they see. The social media giant is allowing users to have a say ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

It supports client-wise data partitioning and federated learning with feature selection for high-dimensional tabular datasets like IoT-IDS or spam classification. spambase-fed-bfa.ipynb Federated BFA ...

Abstract: In multiobjective feature selection, different feature subsets with the same number of selected features can achieve identical classification accuracy, meaning that it is a multimodal ...

Feature engineering is a deal breaker for the success of a machine learning model. It involves turning raw data into meaningful input for algorithms, bridging the gap between simply collecting data ...

Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high ...