Semi-decentralized Federated Ego Graph Learning for Recommendation

no code implementations • 10 Feb 2023 • Liang Qu, Ningzhi Tang, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi, Hongzhi Yin

In light of this, we propose a semi-decentralized federated ego graph learning framework for on-device recommendations, named SemiDFEGL, which introduces new device-to-device collaborations to improve scalability and reduce communication costs and innovatively utilizes predicted interacted item nodes to connect isolated ego graphs to augment local subgraphs such that the high-order user-item collaborative information could be used in a privacy-preserving manner.

Collaborative Filtering Graph Learning +2

Single-shot Embedding Dimension Search in Recommender System

no code implementations • 7 Apr 2022 • Liang Qu, Yonghong Ye, Ningzhi Tang, Lixin Zhang, Yuhui Shi, Hongzhi Yin

In order to alleviate the above issues, some works focus on automated embedding dimension search by formulating it as hyper-parameter optimization or embedding pruning problems.

Click-Through Rate Prediction Recommendation Systems