Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization

arXiv:2403.00798v1 Announce Type: cross
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?
In this paper, we approach the problem of CTR prediction …

abstract advertising arxiv benchmark click cs.ir cs.lg current eigenvalue focus helen improvements online advertising performance prediction prediction models rate recommendation regularization researchers significance through type wise