Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization
Year: 2024
Type: conference-paper
Abstract: Click-Through Rate (CTR) prediction holds paramount significance in online advertising and recommendation scenarios. Despite the proliferation of recent CTR prediction models, the improvements in performance have remained limited, as evidenced by open-source benchmark assessments. Current researchers tend to focus on developing new models for various datasets and settings, often neglecting a crucial question: What is the key challenge that truly makes CTR prediction so demanding?
Source: ACM Web Conference (WWW)
Authors: Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You
Institutions: National University of Singapore, Huawei Technologies (China)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4392489944