1 citations · 1 across the 4 of their papers we have counts for
4 papers
GPR: Towards a Generative Pre-trained One-Model Paradigm for Large-Scale Advertising Recommendation
Jun Zhang, Yi Li, Yue Liu +19
As an intelligent infrastructure connecting users with commercial content, advertising recommendation systems play a central role in information flow and value creation within the…
Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation
Chendi Ge, Xin Wang, Ziwei Zhang +6
Cross-domain recommendation (CDR) mitigates data sparsity and cold-start issues in recommendation systems. While recent CDR approaches using graph neural networks (GNNs) capture co…
AdaS&S: a One-Shot Supernet Approach for Automatic Embedding Size Search in Deep Recommender System
He Wei, Yuekui Yang, Yang Zhang +3
Deep Learning Recommendation Model(DLRM)s utilize the embedding layer to represent various categorical features. Traditional DLRMs adopt unified embedding size for all features, le…
FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization
Yang Zhang, Haiyang Wu, Yuekui Yang
Given a Hyperparameter Optimization(HPO) problem, how to design an algorithm to find optimal configurations efficiently? Bayesian Optimization(BO) and the multi-fidelity BO methods…