4 papers · 1 filter
Federated Automated Feature Engineering
Tom Overman, Diego Klabjan
Automated feature engineering (AutoFE) is used to automatically create new features from original features to improve predictive performance without needing significant human inter…
Continuous-Time Analysis of Federated Averaging
Tom Overman, Diego Klabjan
Federated averaging (FedAvg) is a popular algorithm for horizontal federated learning (FL), where samples are gathered across different clients and are not shared with each other o…
IIFE: Interaction Information Based Automated Feature Engineering
Tom Overman, Diego Klabjan, Jean Utke
Automated feature engineering (AutoFE) is the process of automatically building and selecting new features that help improve downstream predictive performance. While traditional fe…
A Primal-Dual Algorithm for Hybrid Federated Learning
Tom Overman, Garrett Blum, Diego Klabjan
Very few methods for hybrid federated learning, where clients only hold subsets of both features and samples, exist. Yet, this scenario is extremely important in practical settings…