126 citations · 227 across the 19 of their papers we have counts for
25 papers
Impression Allocation and Policy Search in Display Advertising
Di Wu, Cheng Chen, Xiujun Chen +5
In online display advertising, guaranteed contracts and real-time bidding (RTB) are two major ways to sell impressions for a publisher. For large publishers, simultaneously selling…
Leaving No One Behind: A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling
Qianqian Zhang, Xinru Liao, Quan Liu +2
Advertisers play an essential role in many e-commerce platforms like Taobao and Amazon. Fulfilling their marketing needs and supporting their business growth is critical to the lon…
Heterogeneous Graph Neural Networks for Large-Scale Bid Keyword Matching
Zongtao Liu, Bin Ma, Quan Liu +2
Digital advertising is a critical part of many e-commerce platforms such as Taobao and Amazon. While in recent years a lot of attention has been drawn to the consumer side includin…
Binary Code based Hash Embedding for Web-scale Applications
Bencheng Yan, Pengjie Wang, Jinquan Liu +4
Nowadays, deep learning models are widely adopted in web-scale applications such as recommender systems, and online advertising. In these applications, embedding learning of catego…
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer
Bencheng Yan, Pengjie Wang, Kai Zhang +4
Embedding learning for categorical features is crucial for the deep learning-based recommendation models (DLRMs). Each feature value is mapped to an embedding vector via an embeddi…
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
Xiangyu Liu, Chuan Yu, Zhilin Zhang +10
In e-commerce advertising, it is crucial to jointly consider various performance metrics, e.g., user experience, advertiser utility, and platform revenue. Traditional auction mecha…