debiasing | BestHub

DataFunSummit

Aug 21, 2024 · Artificial Intelligence

Causal Debiasing in Ant Group Marketing Recommendation: Data Fusion and Backdoor Adjustment

This article introduces causal debiasing techniques for Ant Group's marketing recommendation systems, detailing background biases, causal graph analysis, a meta‑learning data‑fusion model (MDI), backdoor‑adjustment methods, extensive experiments on public and internal datasets, and real‑world deployment results.

Ant GroupRecommendation systemsbackdoor adjustment

0 likes · 16 min read

Causal Debiasing in Ant Group Marketing Recommendation: Data Fusion and Backdoor Adjustment

DataFunTalk

Jan 6, 2024 · Artificial Intelligence

Causal Debiasing Techniques for Recommendation and Marketing Scenarios

This article presents Ant Group's causal debiasing techniques for recommendation and marketing, covering bias background, data‑fusion based MDI model, back‑door adjustment methods, experimental results on public and industry datasets, and practical applications in advertising and e‑commerce.

MarketingRecommendation systemscausal inference

0 likes · 16 min read

Causal Debiasing Techniques for Recommendation and Marketing Scenarios

DataFunSummit

Mar 27, 2023 · Artificial Intelligence

Model-Agnostic Self-Sampling and Bias‑Proxy Decoupling Frameworks for Debiasing Recommendation Systems

This article presents two model‑independent debiasing solutions for recommendation systems—a self‑sampling, self‑training, self‑evaluation framework (SSTE) that balances prediction accuracy and unbiasedness, and a bias‑proxy representation decoupling framework that leverages expert‑selected proxy features to remove harmful bias while preserving useful signals, with extensive offline and online evaluations in financial product recommendation scenarios.

Bias ProxyRecommendation systemsSelf-Sampling

0 likes · 24 min read

Model-Agnostic Self-Sampling and Bias‑Proxy Decoupling Frameworks for Debiasing Recommendation Systems