4 citations · 5 across the 2 of their papers we have counts for
8 papers
Diversity Regularized Interests Modeling for Recommender Systems
Junmei Hao, Jingcheng Shi, Qing Da +4
With the rapid development of E-commerce and the increase in the quantity of items, users are presented with more items hence their interests broaden. It is increasingly difficult…
Delayed Feedback Modeling for the Entire Space Conversion Rate Prediction
Yanshi Wang, Jie Zhang, Qing Da +1
Estimating post-click conversion rate (CVR) accurately is crucial in E-commerce. However, CVR prediction usually suffers from three major challenges in practice: i) data sparsity:…
AliExpress Learning-To-Rank: Maximizing Online Model Performance without Going Online
Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao +8
Learning-to-rank (LTR) has become a key technology in E-commerce applications. Most existing LTR approaches follow a supervised learning paradigm from offline labeled data collecte…
Policy Optimization with Model-based Explorations
Feiyang Pan, Qingpeng Cai, An-Xiang Zeng +5
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…
Speeding up the Metabolism in E-commerce by Reinforcement Mechanism Design
Hua-Lin He, Chun-Xiang Pan, Qing Da +1
In a large E-commerce platform, all the participants compete for impressions under the allocation mechanism of the platform. Existing methods mainly focus on the short-term return…
Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement Learning
Jing-Cheng Shi, Yang Yu, Qing Da +2
Applying reinforcement learning in physical-world tasks is extremely challenging. It is commonly infeasible to sample a large number of trials, as required by current reinforcement…