Research map / Federated learning and privacy / Personalized and heterogeneous FL

Beyond Single Embedding: Modeling User Preferences as Distribution in Federated Recommendation

ICML 2026 · Federated learning and privacy › Personalized and heterogeneous FL · approach: Non-IID federated learning

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Closest papers by meaning

• Learning Multiple User Distributions for Recommendation via Guided Conditional Diffusion (AAAI 2025 · similarity 0.90)
• Preference Diffusion for Recommendation (ICLR 2025 · similarity 0.89)
• Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach (AAAI 2025 · similarity 0.89)
• Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach (AAAI 2025 · similarity 0.89)
• Federated Recommendation with Additive Personalization (ICLR 2024 · similarity 0.88)
• Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation (NeurIPS 2025 · similarity 0.87)