24 citations · 74 across the 20 of their papers we have counts for
5 papers · 1 filter
AIGB: Generative Auto-bidding via Conditional Diffusion Modeling
Jiayan Guo, Yusen Huo, Zhilin Zhang +5
Auto-bidding plays a crucial role in facilitating online advertising by automatically providing bids for advertisers. Reinforcement learning (RL) has gained popularity for auto-bid…
Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding
Haoming Li, Yusen Huo, Shuai Dou +5
In online advertising, advertisers participate in ad auctions to acquire ad opportunities, often by utilizing auto-bidding tools provided by demand-side platforms (DSPs). The curre…
Sustainable Online Reinforcement Learning for Auto-bidding
Zhiyu Mou, Yusen Huo, Rongquan Bai +4
Recently, auto-bidding technique has become an essential tool to increase the revenue of advertisers. Facing the complex and ever-changing bidding environments in the real-world ad…
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 Adaptive Display Exposure for Real-Time Advertising
Weixun Wang, Junqi Jin, Jianye Hao +9
In E-commerce advertising, where product recommendations and product ads are presented to users simultaneously, the traditional setting is to display ads at fixed positions. Howeve…