1 code implementation • 8 Aug 2022 • Qianying Lin, Wen-Ji Zhou, Yanshi Wang, Qing Da, Qing-Guo Chen, Bing Wang
SAM supports efficient training and real-time inference for user behavior sequences with lengths on the scale of thousands.
no code implementations • 29 Sep 2021 • Qianying Lin, Wen-Ji Zhou, Yanshi Wang, Qing Da, Qing-Guo Chen, Bing Wang
Extensive empirical studies show that our method outperforms various state-of-the-art sequential modeling methods on both public and industrial datasets for long sequential user behavior modeling.
no code implementations • 16 Jul 2021 • Yongqing Gao, Guangda Huzhang, Weijie Shen, Yawen Liu, Wen-Ji Zhou, Qing Da, Yang Yu
Recent E-commerce applications benefit from the growth of deep learning techniques.
no code implementations • 25 Mar 2020 • Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Yawen Liu, Weijie Shen, Wen-Ji Zhou, Qing Da, An-Xiang Zeng, Han Yu, Yang Yu, Zhi-Hua Zhou
The framework consists of an evaluator that generalizes to evaluate recommendations involving the context, and a generator that maximizes the evaluator score by reinforcement learning, and a discriminator that ensures the generalization of the evaluator.
no code implementations • 6 Feb 2020 • Wen-Ji Zhou, Yang Yu
Hierarchical reinforcement learning (HRL) helps address large-scale and sparse reward issues in reinforcement learning.
no code implementations • 31 May 2019 • Wen-Ji Zhou, Yang Yu, Yingfeng Chen, Kai Guan, Tangjie Lv, Changjie Fan, Zhi-Hua Zhou
Experience reuse is key to sample-efficient reinforcement learning.