5 citations · 8 across the 9 of their papers we have counts for
9 papers
HOB: A Holistically Optimized Bidding Strategy under Heterogeneous Bidding Environments
Qi Li, Wendong Huang, Qichen Ye +9
Optimizing a single advertising campaign across heterogeneous channels is a central challenge in industrial autobidding. Auction mechanisms vary across channels in ranking rules (p…
VAO: Validation-Aligned Optimization for Cross-Task Generative Auto-Bidding
Yiqin Lv, Zhiyu Mou, Miao Xu +9
Generative auto-bidding has demonstrated strong performance in online advertising, yet it often suffers from data scarcity in small-scale settings with limited advertiser participa…
Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search
Zhiyu Mou, Yiqin Lv, Miao Xu +9
Auto-bidding is a critical tool for advertisers to improve advertising performance. Recent progress has demonstrated that AI-Generated Bidding (AIGB), which learns a conditional ge…
Permutation Equivariant Model-based Offline Reinforcement Learning for Auto-bidding
Zhiyu Mou, Miao Xu, Wei Chen +3
Reinforcement learning (RL) for auto-bidding has shifted from using simplistic offline simulators (Simulation-based RL Bidding, SRLB) to offline RL on fixed real datasets (Offline…
Large-Scale Auto-bidding with Nash Equilibrium Constraints
Zhiyu Mou, Miao Xu, Rongquan Bai +4
Auto-bidding has become a cornerstone of modern online advertising platforms, enabling many advertisers to automate bidding at scale and optimize campaign performance. However, pre…
Millimeter Wave Wireless Communication Assisted Three-Dimensional Simultaneous Localization and Mapping
Zhiyu Mou, Feifei Gao
In this paper, we study the three-dimensional (3D) simultaneous localization and mapping (SLAM) problem in complex outdoor and indoor environments based only on millimeter-wave (mm…
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…
Cluster Head Detection for Hierarchical UAV Swarm With Graph Self-supervised Learning
Zhiyu Mou, Jun Liu, Xiang Yun +2
In this paper, we study the cluster head detection problem of a two-level unmanned aerial vehicle (UAV) swarm network (USNET) with multiple UAV clusters, where the inherent follow…
Resilient UAV Swarm Communications with Graph Convolutional Neural Network
Zhiyu Mou, Feifei Gao, Jun Liu +1
In this paper, we study the self-healing problem of unmanned aerial vehicle (UAV) swarm network (USNET) that is required to quickly rebuild the communication connectivity under unp…