1 code implementation • 25 Oct 2022 • PengTao Zhang, Junlin Zhang
In this paper, we propose multi-Hash Codebook NETwork (HCNet) as the memory mechanism for efficiently learning and memorizing representations of cross features in CTR tasks.
Ranked #1 on Click-Through Rate Prediction on KDD12
4 code implementations • 12 Sep 2022 • PengTao Zhang, Zheng Zheng, Junlin Zhang
Click-Through Rate (CTR) estimation has become one of the most fundamental tasks in many real-world applications and various deep models have been proposed.
Ranked #16 on Click-Through Rate Prediction on Criteo
3 code implementations • 26 Jul 2021 • Zhiqiang Wang, Qingyun She, PengTao Zhang, Junlin Zhang
In this paper, We propose a novel CTR Framework named ContextNet that implicitly models high-order feature interactions by dynamically refining each feature's embedding according to the input context.
Ranked #15 on Click-Through Rate Prediction on Criteo
1 code implementation • 23 Jun 2020 • Zhiqiang Wang, Qingyun She, PengTao Zhang, Junlin Zhang
Normalization has become one of the most fundamental components in many deep neural networks for machine learning tasks while deep neural network has also been widely used in CTR estimation field.