News
20 Apr2018
A full paper about word embedding was accepted by ACL2018, equal contribution with Xinxin.
16 Apr2018
A full paper Approximating Word Ranking and Negative Sampling for Word Embedding was accepted by IJCAI2018, equal contribution with Guibing Guo and Shichang Ouyang.
10 Dec 2016
A full paper Boosted Factorization Machines for top-N Feature-based Recommendations was accepted by ACM IUI2017.
7 Nov. 2016
We won the Best Studeng Paper Award (5/157) in ICTAI16 after the presentation of our work.
29 Oct. 2016
I am travelling to San Jose for ICTAI16 and will present our work GeoBPR.
24 Oct. 2016
I am travelling to Indianapolis for CIKM16 and will present our work LambdaFM.
27 Sep. 2016
I am invited to be the reviewer of European Conference on Information Retrieval (ECIR 2017).
24 Aug. 2016
Our work Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation is accepted by ICTAI as a full paper.
14 July 2016
Our work LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates is accepted by CIKM as a full paper.
31 Aug. 2015
I am travelling to thessaloniki,Greece for The European Summer School in Information Retrieval (ESSIR 2015) .
Tweets by @duguyuan
Copyright@Webpage template is from Weinan Zhang.
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Fajie Yuan
Assistant Professor
AI division, Westlake University
Hangzhou, China
Email: yuanfajie[AT]westlake.edu.cn
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Before joining Westlake University, Fajie was a senior AI researcher at Tencent, working on recommender systems and user modeling. He obtained his Ph.D. degree at University of Glasgow, advised by Prof. Joemon Jose in 2018. Between 2017 and 2018, He was also a visiting scholar at National University of Singapore, supported by Jim Gatheral Travel Scholarship, and research intern at Telefonic Research in Barcelona, mentored by Dr. Alexandros Karatzoglou and Dr. Ioannis Arapakis. He has published 20 research papers in premier AI conferences as the first/co-first author. Several of his AI algorithms were applied in real production systems, such as LambdaFM (CIKM2016), NextItNet (WSDM2019), and PeterRec (SIGIR2020). At Westlake, he worked as an independent PI, focusing on two major research directions: deep learning (for recommender systems) and AI+Life Science. He often works as reviewers for premier IR and Recommendation conferences, such as NeurIPS, SIGIR, KDD, WSDM, CIKM, WWW, and Recsys etc. His lab is now recruiting self-motivated interns / full-time (posdoc/assistant/associate) researchers/ PHD students in machine learning and Life AI. 西湖大学原发杰团队长期招聘：推荐系统和生物信息（尤其蛋白质相关）方向 ，科研助理，博士生 （2023年有4个PHD名额），博后，访问学者，助理研究员系列。 可以提前联系我，如果你想要申请我的PHD！ He is also open to various collaborations. If you are interested in, please drop an email.
Talk
| Learning Universal User Representations in Recommender Systems |
Large-scale Recommendation DataSets
Selected Publications [Google Scholar]
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Exploring the Upper Limits of Text-Based
Collaborative Filtering Using Large Language
Models: Discoveries and Insights
R. Li, W. Deng, Yu. Cheng, Z. Yuan, J. Zhang, F. Yuan# . ID vs. GPT-3, 175B的GPT-3能否打败最简单的ID？ Preprint. Codes (Soon) |
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Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
J. Fu, F. Yuan# , Y. Song, Z. Yuan, M. Cheng, etc. 系统研究Adapter对于推荐系统迁移学习的影响 Preprint. Codes (Soon) |
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Where to Go Next for Recommender Systems? ID- vs.Modality-based recommender models revisited
Z. Yuan*, F. Yuan* (co-first authors) , Y. Song, etc. 推荐系统何去何从，ID是否有望继续主导推荐系统社区？ SIGIR2023 (CORE rank A*) Codes |
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Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems
G. Yuan*, F. Yuan* (co-first authors) , B. Kong, etc. 一个大规模的推荐系统数据集,覆盖10个任务。 NeurlPS2022 (CORE rank A*) Codes |
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Ultra-Accurate Classification and Discovery of Functional Protein-Coding Genes from Microbiomes Using FunGeneTyper: An Expandable Deep Learning-Based Framework
G. Zhang*, H. Wang* ,..., F. Yuan# , F. Ju# preprint Codes (soon) |
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Exploring evolution-based & -free protein language models as protein function predictors
M. Hu*, F. Yuan* (co-first authors) , K. Yang, etc. 首次探究AlphaFold's Evoformer蛋白质功能预测能力。 NeurlPS2022 (CORE rank A*) Codes |
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Protein Language Model Predicts Mutation Pathogenicity and Clinical Prognosis
X Liu, X Yang, L Ouyang, G Guo, J Su, R Xi*, K Yuan*, F. Yuan# 首次发现蛋白质语言模型具有预测基因突变致癌性和临床生存期。 NeurlPS2022 LMRL workshop Codes (soon) |
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Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search
L. Chen, F. Yuan , J. Yang, M. Yang, C. Li Preprint. Codes (Soon) |
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Enhancing Top-N Item Recommendations by Peer Collaboration
Y. Sun*, F. Yuan* (co-first authors), M. Yang, A. Karatzoglou, L.Shen, x. Zhao SIGIR2022 (short). Codes |
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User-specific Adaptive Fine-tuning for Cross-domain Recommendations
L. Chen*, F. Yuan* (co-first authors), J. Yang, X. He, C. Li, M. Yang TKDE 2021 (CORE rank A*). Codes (Soon) |
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CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network
S. Qu*, F. Yuan* (co-first authors), G. Guo, L. Zhang, W. Wei TKDE 2021 (CORE rank A*). Codes |
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One Person, One Model, One World: Learning Continual User Representation without Forgetting
F. Yuan, G. Zhang, A. Karatzoglou, J. Jose, etc. 首次提出通用用户表征终生学习问题。 SIGIR 2021 (Accept rate: 21%) (CORE rank A*). Codes Slide |
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StackRec: Efficient Training of Very Deep Sequential Recommender Models by Layer Stacking
J. Wang*, F. Yuan* (co-first authors), J. Chen, Q. Wu, C. Li, M. Yang, Y. Sun, G. Zhang SIGIR 2021 (Accept rate: 21%) (CORE rank A*). Codes |
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Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement
M. Cheng*, F. Yuan* (co-first authors), Q. Liu, S. Ge, Z. Li, R. Yu, D. Lian, S. Yuan, En, Chen SIGIR 2021 (Accept rate: 21%) (CORE rank A*). Codes (Soon) |
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Iterative Pruning with Adaptive Regularization for Lifelong Sentiment Classification
B. Geng, M, Yang, F. Yuan , S. Wang, X. Ao, R. Xu SIGIR 2021 (Accept rate: 21%) (CORE rank A*). Codes |
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Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training
M. Cheng*, F. Yuan* (co-first authors), Q. Liu, S. Ge, X. Xin, En, Chen ICDM 2021 (Accept rate: 9.9%) (CORE rank A*). Codes (Soon) |
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SkipRec: A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models
L. Chen*, F. Yuan* (co-first authors), M. Yang, etc. 首次发现推荐系统可以加深到100层。 AAAI 2021 (Accept rate: 21%) (CORE rank A*). Codes Slide |
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Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking
B. Geng, F. Yuan , Q. Xu, Y. Shen, R. Xu, M, Yang, ACL 2021 (Short Paper) (CORE rank A*). Codes |
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Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
F. Yuan, X. He, A. Karatzoglou, etc. 首次发现自监督学习可以学到通用用户表征. SIGIR 2020 (Accept rate: 26%) (CORE rank A*). Codes Slide post |
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A Generic Network Compression Framework for Sequential Recommender Systems
Y. Sun*, F. Yuan* (co-first authors), M. Yang, G. Wei, Z. Zhao, D, Liu SIGIR 2020 (Accept rate: 26%) (CORE rank A*). Codes post |
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Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation
F. Yuan, X. He, H.Jiang, G. Guo, J. Xiong, Z. Xu, Y. Xiong WWW 2020 (Accept rate: 19%) (CORE rank A*). Codes Slide post |
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VSE-fs: Fast Full-Sample Visual Semantic Embedding
S. Zhai, G. Guo, F. Yuan,Y. Liu, X. Wang IEEE Intelligent Systems (CORE rank A). |
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A Simple Convolutional Generative Network for Next Item Recommendation
F. Yuan, A. Karatzoglou, I. Arapakis, J. Jose, X. He. 首次应用空洞卷积于推荐系统。 WSDM 2019 (Accept rate: 16%) (CORE rank A*). Codes Slide post |
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Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation
G. Guo, S. Ouyang, X. He, F. Yuan, X. Liu IJCAI 2019.(Accept rate: 17.9%)(CORE rank A*). Codes post |
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Modeling Embedding Dimension Correlations via
Convolutional Neural Collaborative Filtering
X. Du, X. He, F. Yuan, J. Tang, Z. Qin, T. Chua TOIS 2019 (CORE rank A) Codes |
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Adversarial Training Towards Robust Multimedia Recommender System
J. Tang, X. He, X. Du, F. Yuan, Q. Tian, T. Chua TKDE 2019 (CORE rank A*). Codes |
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Learning Implicit Recommenders from Massive Unobserved Feedback
F. Yuan Phd thesis (preprint) |
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fBGD: Learning Embeddings From Positive Unlabeled Data with BGD
F. Yuan,X. Xin, X. He, G. Guo, W.Zhang, T. Chua, J. Jose UAI 2018. (Accept rate: 30%)(CORE rank A*). Codes post |
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Batch IS NOT Heavy: Learning Word Representations From All Samples
X. Xin*, F. Yuan* (co-first authors), X. He, J. Jose ACL 2018.(Accept rate: 24.8%)(CORE rank A*). Codes |
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Approximating Word Ranking and Negative Sampling for Word Embedding
G. Guo*, SC.Ouyang*,F. Yuan* (co-first authors) IJCAI 2018.(Accept rate: 20.4%)(CORE rank A*). Codes |
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Improving Negative Sampling for Word Representation using Self-embedded Features
L. Chen*, F. Yuan*(co-first authors), J. Jose, W.Zhang WSDM 2018.(Accept rate: 16%)(CORE rank A*). |
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BoostFM: Boosted Factorization Machines for top-N Feature-based Recommendation
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang ACM IUI 2017(Accept rate: 23%)(CORE rank A). |
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A Semantic Graph-Based Approach for Mining Common Topics From Multiple Asynchronous Text Streams
L. Chen, J. Jose, H. Yu, F.Yuan WWW 2017. (Accept rate: 17%)(CORE rank A*). |
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LTRo: Learning to Route Queries in Clustered P2P IR
R. Alkhawaldeh, J. Jose, Deepak P, F.Yuan ECIR 2017 (short paper)(CORE rank B). |
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A Concise Integer Linear Programming Formulation for Implicit Search Result Diversification
H. Yu, A. Jatowt, R. Blanco, H. Joho, J. Jose, L. Chen, F.Yuan WSDM 2017. (Accept rate: 15.8%)(CORE rank A*). |
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LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang CIKM 2016. (Accept rate: 17.6%) (CORE rank A) Code post Applied in Tencent (腾讯) Recommender Systems. |
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Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation
F. Yuan, J. Jose, G. Guo, L. Chen, H. Yu, R. Alkhawaldeh ICTAI 2016. (CORE rank B) (Best Student Paper Award) |
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Optimizing Factorization Machines for Top-N Context-aware Recommendations
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang WISE 2016 (CORE rank B). |
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A Semantic Graph based Topic Model for Question Retrieval in Community Question Answering
L. Chen, J. Jose, H. Yu, F.Yuan, D.Zhang WSDM 2016. (Accept rate: 18.2%) (CORE rank A*) |
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Probabilistic Topic Modelling with Semantic Graph
L. Chen, J. Jose, H. Yu, F.Yuan ECIR 2016. (Accept rate: 21%) (CORE rank B) |
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A New Strategy of Storage and Retrieval for Massive Remote Sensing Data Based on Embedded Database Files
F. Yuan, W. Gao, X.Huang, F.Huang, T.Yu, Y.Zhu International Journal of Advancements in Computing Technology 2012. |