27 citations · 53 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 27 cited
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval
Tao Wu, Ellie Ka-In Chio, Heng-Tze Cheng +15
Many recent advances in neural information retrieval models, which predict top-K items given a query, learn directly from a large training set of (query, item) pairs. However, they…
cs.IR2020★ 2 cited
Modeling Information Need of Users in Search Sessions
Kishaloy Halder, Heng-Tze Cheng, Ellie Ka In Chio +3
Users issue queries to Search Engines, and try to find the desired information in the results produced. They repeat this process if their information need is not met at the first p…
cs.LG2019★ 24 cited
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
Eugene Ie, Vihan Jain, Jing Wang +10
Most practical recommender systems focus on estimating immediate user engagement without considering the long-term effects of recommendations on user behavior. Reinforcement learni…