Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising X Liu, C Yu, Z Zhang, Z Zheng, Y Rong, H Lv, D Huo, Y Wang, D Chen, ... KDD 2021, 3354–3364, 2021 | 60 | 2021 |
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising X Liu, Z Zhang, Z Zheng, C Zhang, M Xu, J Pan, C Yu, F Wu, J Xu, K Gai WSDM 2021, 993-1001, 2021 | 28* | 2021 |
Feudal latent space exploration for coordinated multi-agent reinforcement learning X Liu, Y Tan IEEE Transactions on Neural Networks and Learning Systems 34 (10), 7775-7783, 2022 | 19 | 2022 |
Attentive relational state representation in decentralized multiagent reinforcement learning X Liu, Y Tan IEEE Transactions on Cybernetics 52 (1), 252-264, 2020 | 19 | 2020 |
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising C Wen, M Xu, Z Zhang, Z Zheng, Y Wang, X Liu, Y Rong, D Xie, X Tan, ... WSDM 2022, 1129-1139, 2022 | 17 | 2022 |
On Designing a Two-stage Auction for Online Advertising Y Wang, X Liu, Z Zheng, Z Zhang, M Xu, C Yu, F Wu WWW 2022, 90-99, 2022 | 13 | 2022 |
Adaptive potential fields model for solving distributed area coverage problem in swarm robotics X Liu, Y Tan ICSI 2017, 149-157, 2017 | 7 | 2017 |
Multi-source, multi-object and multi-domain (M-SOD) electromagnetic interference system optimised by intelligent optimisation approaches Y Hu, M Li, X Liu, Y Tan Natural computing 19 (4), 713-732, 2020 | 4 | 2020 |
Personalized Language Model Learning on Text Data Without User Identifiers Y Ding, Y Tan, X Liu, C Niu, F Meng, J Zhou, N Liu, F Wu, G Chen KDD 2025, 2025 | | 2025 |
Feudal Latent Space Exploration for Coordinated Multi-agent Reinforcement Learning X Liu, Y Tan AAMAS 2020 (ALA@AAMAS), 2020 | | 2020 |
Learning Distributed Coordinated Policy in Catching Game with Multi-Agent Reinforcement Learning X Liu, Y Tan IJCNN 2019, 1-7, 2019 | | 2019 |