activity
20192023
most citedProduct Knowledge Graph Embedding for E-commerce

72 citations · 189 across the 18 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.IR2021★ 3 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.IR2021★ 2 cited

Towards the D-Optimal Online Experiment Design for Recommender Selection

Da Xu, Chuanwei Ruan, Evren Korpeoglu +2

Selecting the optimal recommender via online exploration-exploitation is catching increasing attention where the traditional A/B testing can be slow and costly, and offline evaluat…

cs.CL2021★ 1 cited

An Efficient Group-based Search Engine Marketing System for E-Commerce

Cheng Jie, Da Xu, Zigeng Wang +2

With the increasing scale of search engine marketing, designing an efficient bidding system is becoming paramount for the success of e-commerce companies. The critical challenges f…

cs.LG2021★ 1 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.LG2021★ 13 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…

cs.LG2021

Theoretical Understandings of Product Embedding for E-commerce Machine Learning

Da Xu, Chuanwei Ruan, Evren Korpeoglu +2

Product embeddings have been heavily investigated in the past few years, serving as the cornerstone for a broad range of machine learning applications in e-commerce. Despite the em…