Cold-Start Active Preference Learning in Socio-Economic Domains

TL;DR

This paper introduces a PCA-based self-supervised initialization method for active preference learning in socio-economic domains, effectively addressing the cold-start problem and improving performance without requiring expert input.

Contribution

The paper presents a novel PCA-driven self-supervised approach to initialize active preference learning, reducing cold-start issues in socio-economic preference modeling.

Findings

PCA-based initialization outperforms standard methods in cold-start scenarios

The approach is effective across multiple socio-economic datasets

It provides a computationally efficient, expert-free starting point for active learning

Abstract

Active preference learning offers an efficient approach to modeling preferences, but it is hindered by the cold-start problem, which leads to a marked decline in performance when no initial labeled data are available. While cold-start solutions have been proposed for domains such as vision and text, the cold-start problem in active preference learning remains largely unexplored, underscoring the need for practical, effective methods. Drawing inspiration from established practices in social and economic research, the proposed method initiates learning with a self-supervised phase that employs Principal Component Analysis (PCA) to generate initial pseudo-labels. This process produces a \say{warmed-up} model based solely on the data's intrinsic structure, without requiring expert input. The model is then refined through an active learning loop that strategically queries a simulated noisy oracle for labels. Experiments conducted on various socio-economic datasets, including those related to financial credibility, career success rate, and socio-economic status, consistently show that the PCA-driven approach outperforms standard active learning strategies that start without prior information. This work thus provides a computationally efficient and straightforward solution that effectively addresses the cold-start problem.