activity
20192022
most citedProduct Knowledge Graph Embedding for E-commerce

72 citations · 175 across the 12 of their papers we have counts for

collaborators

13 papers

cs.IR20222 cited

Tutorial: Modern Theoretical Tools for Understanding and Designing Next-generation Information Retrieval System

Da Xu, Chuanwei Ruan

In the relatively short history of machine learning, the subtle balance between engineering and theoretical progress has been proved critical at various stages. The most recent wav…

cs.IR20221 cited

From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation

Da Xu, Yuting Ye, Chuanwei Ruan

The interventional nature of recommendation has attracted increasing attention in recent years. It particularly motivates researchers to formulate learning and evaluating recommend…

cs.LG2022

Towards Robust Off-policy Learning for Runtime Uncertainty

Da Xu, Yuting Ye, Chuanwei Ruan +1

Off-policy learning plays a pivotal role in optimizing and evaluating policies prior to the online deployment. However, during the real-time serving, we observe varieties of interv…

cs.IR20213 cited

Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives

Da Xu, Chuanwei Ruan, Evren Korpeoglu +2

The recent work by Rendle et al. (2020), based on empirical observations, argues that matrix-factorization collaborative filtering (MCF) compares favorably to neural collaborative…

cs.LG20211 cited

A Temporal Kernel Approach for Deep Learning with Continuous-time Information

Da Xu, Chuanwei Ruan, Evren Korpeoglu +2

Sequential deep learning models such as RNN, causal CNN and attention mechanism do not readily consume continuous-time information. Discretizing the temporal data, as we show, caus…

cs.LG202113 cited

Understanding the role of importance weighting for deep learning

Da Xu, Yuting Ye, Chuanwei Ruan

The recent paper by Byrd & Lipton (2019), based on empirical observations, raises a major concern on the impact of importance weighting for the over-parameterized deep learning mod…