5 citations · 8 across the 11 of their papers we have counts for
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…
Reverse Prompt Engineering
Hanqing Li, Diego Klabjan
We explore a new language model inversion problem under strict black-box, zero-shot, and limited data conditions. We propose a novel training-free framework that reconstructs promp…
Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient
Yintai Ma, Diego Klabjan, Jean Utke
The development of sophisticated models for video-to-video synthesis has been facilitated by recent advances in deep reinforcement learning and generative adversarial networks (GAN…
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…