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20212023
most citedMulti-Task Recommendations with Reinforcement Learning

45 citations · 116 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023★ 2 cited

State Regularized Policy Optimization on Data with Dynamics Shift

Zhenghai Xue, Qingpeng Cai, Shuchang Liu +4

In many real-world scenarios, Reinforcement Learning (RL) algorithms are trained on data with dynamics shift, i.e., with different underlying environment dynamics. A majority of cu…

cs.LG2023★ 4 cited

Reinforcing User Retention in a Billion Scale Short Video Recommender System

Qingpeng Cai, Shuchang Liu, Xueliang Wang +6

Recently, short video platforms have achieved rapid user growth by recommending interesting content to users. The objective of the recommendation is to optimize user retention, the…

cs.LG2023★ 2 cited

Two-Stage Constrained Actor-Critic for Short Video Recommendation

Qingpeng Cai, Zhenghai Xue, Chi Zhang +9

The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users sequentially intera…

cs.LG2022★ 5 cited

Constrained Reinforcement Learning for Short Video Recommendation

Qingpeng Cai, Ruohan Zhan, Chi Zhang +5

The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users provide complex and…

cs.LG2021

PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic

Weicong Ding, Hanlin Tang, Jingshuo Feng +17

Real-world recommendation systems often consist of two phases. In the first phase, multiple predictive models produce the probability of different immediate user actions. In the se…