activity
20192026
most citedA Comprehensive Survey on Transfer Learning

227 citations · 461 across the 14 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.LG2021

Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification

Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +4

Recent years have witnessed the increasing popularity of Location-based Social Network (LBSN) services, which provides unparalleled opportunities to build personalized Point-of-Int…

cs.LG2021★ 2 cited

Neural Hierarchical Factorization Machines for User's Event Sequence Analysis

Dongbo Xi, Fuzhen Zhuang, Bowen Song +6

Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular…

cs.CL2021★ 7 cited

Domain Adaptation with Category Attention Network for Deep Sentiment Analysis

Dongbo Xi, Fuzhen Zhuang, Ganbin Zhou +3

Domain adaptation tasks such as cross-domain sentiment classification aim to utilize existing labeled data in the source domain and unlabeled or few labeled data in the target doma…

cs.LG2021★ 13 cited

Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification

Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3

Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…

cs.AI2021★ 7 cited

Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising

Dongbo Xi, Zhen Chen, Peng Yan +4

In most real-world large-scale online applications (e.g., e-commerce or finance), customer acquisition is usually a multi-step conversion process of audiences. For example, an impr…

cs.IR2021★ 122 cited

Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users

Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang +5

Cold-start problems are enormous challenges in practical recommender systems. One promising solution for this problem is cross-domain recommendation (CDR) which leverages rich info…