Search Results for author: Fangye Wang

Found 4 papers, 4 papers with code

A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction

1 code implementation8 Nov 2023 Fangye Wang, Hansu Gu, Dongsheng Li, Tun Lu, Peng Zhang, Li Shang, Ning Gu

In addition, we present a new architecture of assigning independent FR modules to separate sub-networks for parallel CTR models, as opposed to the conventional method of inserting a shared FR module on top of the embedding layer.

Benchmarking Click-Through Rate Prediction

CL4CTR: A Contrastive Learning Framework for CTR Prediction

1 code implementation1 Dec 2022 Fangye Wang, Yingxu Wang, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu

Many Click-Through Rate (CTR) prediction works focused on designing advanced architectures to model complex feature interactions but neglected the importance of feature representation learning, e. g., adopting a plain embedding layer for each feature, which results in sub-optimal feature representations and thus inferior CTR prediction performance.

Click-Through Rate Prediction Contrastive Learning +3

Enhancing CTR Prediction with Context-Aware Feature Representation Learning

1 code implementation19 Apr 2022 Fangye Wang, Yingxu Wang, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu

However, most methods only learn a fixed representation for each feature without considering the varying importance of each feature under different contexts, resulting in inferior performance.

Click-Through Rate Prediction Representation Learning

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