10 citations · 18 across the 6 of their papers we have counts for
6 papers
Sparse Attentive Memory Network for Click-through Rate Prediction with Long Sequences
Qianying Lin, Wen-Ji Zhou, Yanshi Wang +3
Sequential recommendation predicts users' next behaviors with their historical interactions. Recommending with longer sequences improves recommendation accuracy and increases the d…
Imitate TheWorld: A Search Engine Simulation Platform
Yongqing Gao, Guangda Huzhang, Weijie Shen +4
Recent E-commerce applications benefit from the growth of deep learning techniques. However, we notice that many works attempt to maximize business objectives by closely matching o…
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…
Temporal-adaptive Hierarchical Reinforcement Learning
Wen-Ji Zhou, Yang Yu
Hierarchical reinforcement learning (HRL) helps address large-scale and sparse reward issues in reinforcement learning. In HRL, the policy model has an inner representation structu…
Reinforcement Learning Experience Reuse with Policy Residual Representation
Wen-Ji Zhou, Yang Yu, Yingfeng Chen +4
Experience reuse is key to sample-efficient reinforcement learning. One of the critical issues is how the experience is represented and stored. Previously, the experience can be st…
Viewpoint Selection for Photographing Architectures
Jingwu He, Linbo Wang, Wenzhe Zhou +3
This paper studies the problem of how to choose good viewpoints for taking photographs of architectures. We achieve this by learning from professional photographs of world famous l…