5 citations · 18 across the 12 of their papers we have counts for
12 papers
InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization
Jiarui Jin, Zexue He, Mengyue Yang +4
Ranking items regarding individual user interests is a core technique of multiple downstream tasks such as recommender systems. Learning such a personalized ranker typically relies…
Lending Interaction Wings to Recommender Systems with Conversational Agents
Jiarui Jin, Xianyu Chen, Fanghua Ye +5
Recommender systems trained on offline historical user behaviors are embracing conversational techniques to online query user preference. Unlike prior conversational recommendation…
Who to Watch Next: Two-side Interactive Networks for Live Broadcast Recommendation
Jiarui Jin, Xianyu Chen, Yuanbo Chen +5
With the prevalence of live broadcast business nowadays, a new type of recommendation service, called live broadcast recommendation, is widely used in many mobile e-commerce Apps.…
Learn over Past, Evolve for Future: Search-based Time-aware Recommendation with Sequential Behavior Data
Jiarui Jin, Xianyu Chen, Weinan Zhang +3
The personalized recommendation is an essential part of modern e-commerce, where user's demands are not only conditioned by their profile but also by their recent browsing behavior…
Efficient Policy Space Response Oracles
Ming Zhou, Jingxiao Chen, Ying Wen +4
Policy Space Response Oracle methods (PSRO) provide a general solution to learn Nash equilibrium in two-player zero-sum games but suffer from two drawbacks: (1) the computation ine…
AIM: Automatic Interaction Machine for Click-Through Rate Prediction
Chenxu Zhu, Bo Chen, Weinan Zhang +5
Feature embedding learning and feature interaction modeling are two crucial components of deep models for Click-Through Rate (CTR) prediction. Most existing deep CTR models suffer…