재정 지원 요구사항을 통해 공개된 자료 - Tao Qi자세히 알아보기
제공된 곳이 없음: 4
Neural gender prediction in microblogging with emotion-aware user representation
C Wu, F Wu, T Qi, J Liu, Y Huang, X Xie
CIKM 2019, 2401-2404, 2019
재정 지원 요구사항 정책: National Natural Science Foundation of China
Semi-supervised named entity recognition in multi-level contexts
Y Chen, C Wu, T Qi, Z Yuan, Y Zhang, S Yang, J Guan, D Sun, Y Huang
Neurocomputing 520, 194-204, 2023
재정 지원 요구사항 정책: National Natural Science Foundation of China
Detecting entities of works for Chinese chatbot
C Wu, F Wu, T Qi, J Liu, Y Huang, X Xie
TALLIP 19 (6), 1-13, 2020
재정 지원 요구사항 정책: National Natural Science Foundation of China
Fast Neural Chinese Named Entity Recognition with Multi-head Self-attention
T Qi, C Wu, F Wu, S Ge, J Liu, Y Huang, X Xie
CCKS 2019, 98-110, 2019
재정 지원 요구사항 정책: National Natural Science Foundation of China
제공된 곳이 있음: 28
A federated graph neural network framework for privacy-preserving personalization
C Wu, F Wu, L Lyu, T Qi, Y Huang, X Xie
Nature Communications 13 (1), 3091, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
Neural news recommendation with multi-head self-attention
C Wu, F Wu, S Ge, T Qi, Y Huang, X Xie
EMNLP 2019, 6389-6394, 2019
재정 지원 요구사항 정책: National Natural Science Foundation of China
Empowering News Recommendation with Pre-trained Language Models
C Wu, F Wu, T Qi, Y Huang
SIGIR 2021, 2021
재정 지원 요구사항 정책: National Natural Science Foundation of China
Graph enhanced representation learning for news recommendation
S Ge, C Wu, F Wu, T Qi, Y Huang
WWW 2020, 2863-2869, 2020
재정 지원 요구사항 정책: National Natural Science Foundation of China
Personalized News Recommendation with Knowledge-aware Interactive Matching
T Qi, F Wu, C Wu, Y Huang
SIGIR 2021, 2021
재정 지원 요구사항 정책: National Natural Science Foundation of China
Feedrec: News feed recommendation with various user feedbacks
C Wu, F Wu, T Qi, Q Liu, X Tian, J Li, W He, Y Huang, X Xie
Proceedings of the ACM Web Conference 2022, 2088-2097, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
User Modeling with Click Preference and Reading Satisfaction for News Recommendation.
C Wu, F Wu, T Qi, Y Huang
IJCAI 2020, 3023-3029, 2020
재정 지원 요구사항 정책: National Natural Science Foundation of China
Mm-rec: Visiolinguistic model empowered multimodal news recommendation
C Wu, F Wu, T Qi, C Zhang, Y Huang, T Xu
Proceedings of the 45th international ACM SIGIR conference on research and …, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling
C Wu, F Wu, T Qi, Y Huang, X Xie
KDD, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
Reviews meet graphs: Enhancing user and item representations for recommendation with hierarchical attentive graph neural network
C Wu, F Wu, T Qi, S Ge, Y Huang, X Xie
EMNLP 2019, 4884-4893, 2019
재정 지원 요구사항 정책: National Natural Science Foundation of China
Neural news recommendation with heterogeneous user behavior
C Wu, F Wu, M An, T Qi, J Huang, Y Huang, X Xie
EMNLP 2019, 4874-4883, 2019
재정 지원 요구사항 정책: National Natural Science Foundation of China
Sentirec: Sentiment diversity-aware neural news recommendation
C Wu, F Wu, T Qi, Y Huang
AACL 2020, 44-53, 2020
재정 지원 요구사항 정책: National Natural Science Foundation of China
Fairvfl: A fair vertical federated learning framework with contrastive adversarial learning
T Qi, F Wu, C Wu, L Lyu, T Xu, H Liao, Z Yang, Y Huang, X Xie
Advances in neural information processing systems 35, 7852-7865, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
News Recommendation with Candidate-aware User Modeling
T Qi, F Wu, C Wu, Y Huang
SIGIR 2022, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
ProFairRec: Provider Fairness-aware News Recommendation
T Qi, F Wu, C Wu, P Sun, L Wu, X Wang, Y Huang, X Xie
SIGIR 2022, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
Is News Recommendation a Sequential Recommendation Task?
C Wu, F Wu, T Qi, Y Huang
SIGIR, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
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