activity
20182026
most citedReinforcement Learning for Uplift Modeling

6 citations · 12 across the 7 of their papers we have counts for

collaborators

7 papers

cs.GT2026

JD-BP: A Joint-Decision Generative Framework for Auto-Bidding and Pricing

Linghui Meng, Chun Gan, Shengsheng Niu +8

Auto-bidding services optimize real-time bidding strategies for advertisers under key performance indicator (KPI) constraints such as target return on investment and budget. Howeve…

cs.GT2022

No-regret Learning in Repeated First-Price Auctions with Budget Constraints

Rui Ai, Chang Wang, Chenchen Li +3

Recently the online advertising market has exhibited a gradual shift from second-price auctions to first-price auctions. Although there has been a line of works concerning online b…

cs.GT2022

On the Convergence of Fictitious Play: A Decomposition Approach

Yurong Chen, Xiaotie Deng, Chenchen Li +4

Fictitious play (FP) is one of the most fundamental game-theoretical learning frameworks for computing Nash equilibrium in -player games, which builds the foundation for modern…

stat.ML2019★ 2 cited

Cost-Effective Incentive Allocation via Structured Counterfactual Inference

Romain Lopez, Chenchen Li, Xiang Yan +4

We address a practical problem ubiquitous in modern marketing campaigns, in which a central agent tries to learn a policy for allocating strategic financial incentives to customers…

cs.CV2018★ 2 cited

Visual-Texual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks

Chenchen Li, Jialin Wang, Hongwei Wang +3

User emotion analysis toward videos is to automatically recognize the general emotional status of viewers from the multimedia content embedded in the online video stream. Existing…

cs.LG2018★ 6 cited

Reinforcement Learning for Uplift Modeling

Chenchen Li, Xiang Yan, Xiaotie Deng +6

Uplift modeling aims to directly model the incremental impact of a treatment on an individual response. In this work, we address the problem from a new angle and reformulate it as…