11 citations · 28 across the 5 of their papers we have counts for
10 papers
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising
Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng +7
In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform…
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
Chao Du, Zhifeng Gao, Shuo Yuan +7
Modern online advertising systems inevitably rely on personalization methods, such as click-through rate (CTR) prediction. Recent progress in CTR prediction enjoys the rich represe…
Learning to Infer User Hidden States for Online Sequential Advertising
Zhaoqing Peng, Junqi Jin, Lan Luo +11
To drive purchase in online advertising, it is of the advertiser's great interest to optimize the sequential advertising strategy whose performance and interpretability are both im…
A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction
Liyi Guo, Rui Lu, Haoqi Zhang +9
For e-commerce platforms such as Taobao and Amazon, advertisers play an important role in the entire digital ecosystem: their behaviors explicitly influence users' browsing and sho…
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Xiaotian Hao, Zhaoqing Peng, Yi Ma +12
In E-commerce, advertising is essential for merchants to reach their target users. The typical objective is to maximize the advertiser's cumulative revenue over a period of time un…
Learning Optimal Tree Models Under Beam Search
Jingwei Zhuo, Ziru Xu, Wei Dai +4
Retrieving relevant targets from an extremely large target set under computational limits is a common challenge for information retrieval and recommendation systems. Tree models, w…