A Unified Knowledge-Distillation and Semi-Supervised Learning Framework to Improve Industrial Ads Delivery Systems

no code implementations • 5 Feb 2025 • Hamid Eghbalzadeh, Yang Wang, Rui Li, Yuji Mo, Qin Ding, Jiaxiang Fu, Liang Dai, Shuo Gu, Nima Noorshams, Sem Park, Bo Long, Xue Feng

Industrial ads ranking systems conventionally rely on labeled impression data, which leads to challenges such as overfitting, slower incremental gain from model scaling, and biases due to discrepancies between training and serving data.

Knowledge Distillation