Oct 13, 2022 · We propose a sustainable online RL (SORL) framework that trains the auto-bidding policy by directly interacting with the RAS, instead of learning in the VAS.
In this paper, we propose a novel sustainable online reinforcement learning (SORL) framework to address the IBOO challenge. For the first time, the SORL ...
Apr 3, 2024 · We also develop a variance-suppressed conservative Q-learning (V-CQL) method to effectively and stably learn the auto-bidding policy with the ...
Sustainable Online Reinforcement Learning for Auto-bidding
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We designed a deep reinforcement learning (DRL) framework to learn the repetitive transmission patterns of time-sensitive traffic and address potential latency ...
Nov 28, 2022 · Recently, auto-bidding technique has become an essential tool to increase the return on investment (ROI) for advertisers.
sign in. Inproceedings,. Sustainable Online Reinforcement Learning for Auto-bidding. Z. Mou, Y. Huo, R. Bai, M. Xie, C. Yu, J. Xu, and B. Zheng. NeurIPS, (2022 ).
Sustainable Online Reinforcement Learning for Auto-bidding · Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep ...
Sustainable Online Reinforcement Learning for Auto-bidding. CoRR abs/2210.07006 (2022); 2021. [i2]. view. electronic edition @ arxiv.org (open access) ...
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Feb 23, 2024 · Reinforcement learning for auto-bidding. Bid optimization in online advertising is a sequential decision procedure, and can be solved via ...