activity
20162020
most citedJoint Text Embedding for Personalized Content-based Recommendation

20 citations · 53 across the 6 of their papers we have counts for

collaborators

9 papers

stat.AP2020

Causal Meta-Mediation Analysis: Inferring Dose-Response Function From Summary Statistics of Many Randomized Experiments

Zenan Wang, Xuan Yin, Tianbo Li +1

It is common in the internet industry to use offline-developed algorithms to power online products that contribute to the success of a business. Offline-developed algorithms are gu…

stat.AP2019

The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis

Xuan Yin, Liangjie Hong

E-commerce companies have a number of online products, such as organic search, sponsored search, and recommendation modules, to fulfill customer needs. Although each of these produ…

cs.IR20195 cited

Revenue, Relevance, Arbitrage and More: Joint Optimization Framework for Search Experiences in Two-Sided Marketplaces

Andrew Stanton, Akhila Ananthram, Congzhe Su +1

Two-sided marketplaces such as eBay, Etsy and Taobao have two distinct groups of customers: buyers who use the platform to seek the most relevant and interesting item to purchase a…

cs.IR20186 cited

Learning Item-Interaction Embeddings for User Recommendations

Xiaoting Zhao, Raphael Louca, Diane Hu +1

Industry-scale recommendation systems have become a cornerstone of the e-commerce shopping experience. For Etsy, an online marketplace with over 50 million handmade and vintage ite…

cs.IR201715 cited

An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

Kamelia Aryafar, Devin Guillory, Liangjie Hong

Etsy is a global marketplace where people across the world connect to make, buy and sell unique goods. Sellers at Etsy can promote their product listings via advertising campaigns…

cs.LG20174 cited

On Sampling Strategies for Neural Network-based Collaborative Filtering

Ting Chen, Yizhou Sun, Yue Shi +1

Recent advances in neural networks have inspired people to design hybrid recommendation algorithms that can incorporate both (1) user-item interaction information and (2) content i…