Search Results for author: An-Xiang Zeng

Found 11 papers, 3 papers with code

Scenario-aware and Mutual-based approach for Multi-scenario Recommendation in E-Commerce

no code implementations16 Dec 2020 Yuting Chen, Yanshi Wang, Yabo Ni, An-Xiang Zeng, Lanfen Lin

Finally, we employ a novel mutual unit to adaptively learn the similarity between various scenarios and incorporate it into multi-branch network.

Recommendation Systems

Generator and Critic: A Deep Reinforcement Learning Approach for Slate Re-ranking in E-commerce

no code implementations25 May 2020 Jianxiong Wei, An-Xiang Zeng, Yueqiu Wu, Peng Guo, Qingsong Hua, Qingpeng Cai

In this paper, we present a novel Generator and Critic slate re-ranking approach, where the Critic evaluates the slate and the Generator ranks the items by the reinforcement learning approach.

reinforcement-learning Re-Ranking

AliExpress Learning-To-Rank: Maximizing Online Model Performance without Going Online

no code implementations25 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.

Learning-To-Rank

Policy Optimization with Model-based Explorations

no code implementations18 Nov 2018 Feiyang Pan, Qingpeng Cai, An-Xiang Zeng, Chun-Xiang Pan, Qing Da, Hua-Lin He, Qing He, Pingzhong Tang

Model-free reinforcement learning methods such as the Proximal Policy Optimization algorithm (PPO) have successfully applied in complex decision-making problems such as Atari games.

Atari Games Decision Making +2

Speeding up the Metabolism in E-commerce by Reinforcement Mechanism Design

no code implementations2 Jul 2018 Hua-Lin He, Chun-Xiang Pan, Qing Da, An-Xiang Zeng

In a large E-commerce platform, all the participants compete for impressions under the allocation mechanism of the platform.

Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks

no code implementations28 May 2018 Yabo Ni, Dan Ou, Shichen Liu, Xiang Li, Wenwu Ou, An-Xiang Zeng, Luo Si

In this work, we propose to learn universal user representations across multiple tasks for more e ective personalization.

Dual Swap Disentangling

1 code implementation NeurIPS 2018 Zunlei Feng, Xinchao Wang, Chenglong Ke, An-Xiang Zeng, DaCheng Tao, Mingli Song

To achieve disentangling using the labeled pairs, we follow a "encoding-swap-decoding" process, where we first swap the parts of their encodings corresponding to the shared attribute and then decode the obtained hybrid codes to reconstruct the original input pairs.

Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application

1 code implementation2 Mar 2018 Yujing Hu, Qing Da, An-Xiang Zeng, Yang Yu, Yinghui Xu

For better utilizing the correlation between different ranking steps, in this paper, we propose to use reinforcement learning (RL) to learn an optimal ranking policy which maximizes the expected accumulative rewards in a search session.

Decision Making Learning-To-Rank +1

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