activity
20212024
most citedLinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign

2 citations · 5 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2023★ 1 cited

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning

Tianchi Cai, Jiyan Jiang, Wenpeng Zhang +7

We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing b…

cs.LG2023

Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems

Tianchi Cai, Shenliao Bao, Jiyan Jiang +5

Model-free RL-based recommender systems have recently received increasing research attention due to their capability to handle partial feedback and long-term rewards. However, most…

cs.LG2021★ 1 cited

Adversarial Learning for Incentive Optimization in Mobile Payment Marketing

Xuanying Chen, Zhining Liu, Li Yu +5

Many payment platforms hold large-scale marketing campaigns, which allocate incentives to encourage users to pay through their applications. To maximize the return on investment, i…

cs.LG2021

A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning

Tianchi Cai, Wenpeng Zhang, Lihong Gu +2

Although well-established in general reinforcement learning (RL), value-based methods are rarely explored in constrained RL (CRL) for their incapability of finding policies that ca…

cs.LG2021

Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction

Yun Yue, Yongchao Liu, Suo Tong +7

We develop a novel framework that adds the regularizers of the sparse group lasso to a family of adaptive optimizers in deep learning, such as Momentum, Adagrad, Adam, AMSGrad, Ada…