Robust Representation Learning for Unified Online Top-K Recommendation

no code implementations • 24 Oct 2023 • Minfang Lu, Yuchen Jiang, Huihui Dong, Qi Li, Ziru Xu, Yuanlin Liu, Lixia Wu, Haoyuan Hu, Han Zhu, Yuning Jiang, Jian Xu, Bo Zheng

The robust representation learning employs domain adversarial learning and multi-view wasserstein distribution learning to learn robust representations.

Fairness Representation Learning

Adaptive Domain Interest Network for Multi-domain Recommendation

no code implementations • 20 Jun 2022 • Yuchen Jiang, Qi Li, Han Zhu, Jinbei Yu, Jin Li, Ziru Xu, Huihui Dong, Bo Zheng

Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously.

Domain Adaptation Recommendation Systems +1

Construct Informative Triplet with Two-stage Hard-sample Generation

no code implementations • 4 Dec 2021 • Chuang Zhu, Zheng Hu, Huihui Dong, Gang He, Zekuan Yu, Shangshang Zhang

In this paper, we propose a robust sample generation scheme to construct informative triplets.

Generative Adversarial Network Metric Learning +2