4.3k citations · 10.2k across the 68 of their papers we have counts for
3 papers · 2 filters
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation
Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao +3
Highly skewed long-tail item distribution is very common in recommendation systems. It significantly hurts model performance on tail items. To improve tail-item recommendation, we…
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng +4
Learning effective feature crosses is the key behind building recommender systems. However, the sparse and large feature space requires exhaustive search to identify effective cros…
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems
Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen +4
Recommender system models often represent various sparse features like users, items, and categorical features via embeddings. A standard approach is to map each unique feature valu…