Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation

no code implementations • 21 Oct 2023 • Yongjing Hao, Pengpeng Zhao, Junhua Fang, Jianfeng Qu, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou

In this paper, we propose a Meta-optimized Seq2Seq Generator and Contrastive Learning (Meta-SGCL) for sequential recommendation, which applies the meta-optimized two-step training strategy to adaptive generate contrastive views.

Contrastive Learning Sequential Recommendation

Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation

no code implementations • 21 Apr 2022 • Yongjing Hao, Pengpeng Zhao, Xuefeng Xian, Guanfeng Liu, Deqing Wang, Lei Zhao, Yanchi Liu, Victor S. Sheng

To this end, in this paper, we propose a Learnable Model Augmentation self-supervised learning for sequential Recommendation (LMA4Rec).

Data Augmentation Self-Supervised Learning +1