he xiangnan ustc

endobj His research interests span information retrieval, data mining, and multimedia analytics. How to Learn Item Representation for Cold-Start Multimedia Recommendation?. Introduction In this work, we aim to simplify the design of GCN to make it more concise and appropriate for recommendation. His research interests span information retrieval, data mining, and applied machine learning. yet for this period. A Sequential Meta-Learning Method∗ Yang Zhang1, Fuli Feng2, Chenxu Wang1, Xiangnan He1, Meng Wang3, Yan Li4, Yongdong Zhang1 1University of Science and Technology of China, 2National University of Singapore 3Hefei University of Technology, 4Beijing Kuaishou Technology Co., Ltd. Beijing, China {fulifeng93,xiangnanhe}@gmail.com,{zy2015,wcx123}@mail.ustc… 599 0 obj 2020. Xiangnan He University of Science and Technology of China, China xiangnanhe@gmail.com ABSTRACT Time series prediction is an intensively studied topic in data mining. Sort. Xiangnan He School of Information Science and Technology, USTC xiangnanhe@gmail.com Yongfeng Zhang Department of Computer Science Rutgers University … XIANGNAN HE, University of Scinece and Technology of China, China PENG JIANG, Kuaishou Inc., China TAT-SENG CHUA, National University of Singapore, Republic of Singapore Static recommendation methods like collaborative filtering suffer from the inherent limitation of performing real-time personalization for cold-start users. Modeling Personalized Out-of-Town Distances in Location Recommendation Daizong Ding , Mi Zhangz, Xudong Pan , Min Yang , Xiangnan Hey School of Computer Science, Fudan University ySchool of Data Science, University of Science and Technology of China Emails: f17110240010, mi zhang, 18110240010, m yangg@fudan.edu.cn, xiangnanhe@gmail.com E-mail: xiangwang@u.nus.edu and fulifeng93@gmail.com. Xiangnan He, Kuan Deng ,Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang(2020). Python stream ACM, New Woodstock ’18, June 03–05, 2018, W oodstock, NY Tianxin Wei 1, Fuli Feng 2, Jiawei Chen 1, Chufeng Shi 1, Ziwei W u 1, Jinfeng Yi 3, Xiangnan He 1 Figure 5: The framework of MACR. << /Linearized 1 /L 1340490 /H [ 2885 753 ] /O 602 /E 396037 /N 29 /T 1336630 >> Min-Yen Kan (靳民彦) Associate Professor, National University of Singapore Verified email at comp.nus.edu.sg. Xiangnan He, Min-Yen Kan, Peichu Xie, and Xiao Chen. Xiangnan He, Kuan Deng ,Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang(2020). 166, TensorFlow Implementation of Attentional Factorization Machine, Python Xiangnan He University of Science and Technology of China, School of Data Science Verified email at ustc.edu.cn. 416 Title. Xiangnan He. SIGKDD ‘20 PDF@USTC; Dialogue Understanding and Generation: Towards Deep Conversational Recommendations. My research interests span information retrieval, data mining, and multi-media analytics. Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System Tianxin Wei1, Fuli Feng2, Jiawei Chen1, Chufeng Shi1, Ziwei Wu1, Jinfeng Yi3, Xiangnan He1 1University of Science and Technology of China, 2National University of Singapore, 3JD AI Research rouseau@mail.ustc.edu.cn,fulifeng93@gmail.com,cjwustc@ustc.edu.cn Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. 192 Read Xiangnan He's latest research, browse their coauthor's research, and play around with their algorithms ��Y@-�@���(v-�R������-����k���:23T��.8�]-��W`�_4-l�פH�3��CCU�P8�Np,Ƌ��a����h�N�``�e�Ҡ�hN������7��5�e��.�mv7��"����D�3+�f?G���;�Έ1p�0q-nbd�7��d�bV�����)��� Dr. Xiangnan He is a professor with the University of Science and Technology of China (USTC). 598 0 obj Block user. NIPS ‘18 PDF@nips.cc 506, TenforFlow Implementation of Neural Factorization Machine, Python Author: Prof. Xiangnan He (staff.ustc.edu.cn/~hexn/) (Also see Tensorflow implementation) Introduction. "Yրɵ`�+��`r1���w�����.�F�Qr��&�;w��0J�q���a��$ Gv: 600 0 obj SIGIR’19, July 2019, Paris, France Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, and Joemon Jose Figure 1: An example of multiple item relations. Articles Cited by. He Xiangnan hexiangnan. Haoru Wang's 9 research works with 15 citations and 359 reads, including: Electroresistance effect in oxygen-deficient La 0.8 Ba 0.2 MnO 3− δ thin films Xiangnan He Sampling strategies have been widely applied in many recommendation systems to accelerate model learning from implicit feedback data. 1.2k In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2014, Accept rate: 21%), pp. Each re-lation is described with a two-level hierarchy of type and value. Previous models largely follow a general supervised learning paradigm — treating each Verified email at ustc.edu.cn - Homepage. You signed in with another tab or window. Learn more about blocking users. Xiangnan He University of Science and Technology of China hexn@ustc.edu.cn Tat-Seng Chua National University of Singapore dcscts@nus.edu.sg ABSTRACT Recommendation methods construct predictive models to estimate the likelihood of a user-item interaction. Research Fellow with School of Computing, National University of Singapore. endstream %���� LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation, Paper in arXiv. Contact GitHub support about this user’s behavior. Multiple relations may exist between two items and the same value may occur in relations of dierent types. MM ’20, October 12–16, 2020, Seattle, WA, USA Da Cao, Yawen Zeng, Meng Liu, Xiangnan He, Meng Wang, and Zheng Qin Q St A lk t fi t d tk t tbl uery S en t ence: woman wa s o a re f r i gera t or an t a k es ou some vege t a bl es. x�cbd`�g`b``8 "�6�H�� ��#X|���&�H19 �x�D~b��" 2CDޘR�� endstream He received the Ph.D. degree in Computer Science from National University of Singapore (NUS) in 2016. 602 0 obj Xiangnan Xie Hong Zhu Half-Cr-doped YMnO3 single crystal films have been grown on YAlO3 substrates with various compressive strains by using magneto sputtering and ex-situ annealing process. Jun Xu, Gaoling School of Artificial Intelligence, Renmin University of China, China, junxu@ruc.edu.cn Xiangnan He, School of Information Science and Technology, University of Science and Technology of China, China, hexn@ustc.edu.cn Hang Li, Bytedance AI Lab, China, lihang.lh@bytedance.com hexiangnan has no activity wenqiang lei National University of Singapore Verified email at u.nus.edu. In this work, we aim to simplify the design of GCN to make it more concise and appropriate for recommendation. 443 Huangshan Road, Hefei, China 230027 Email: xiangnanhe at gmail.com I lead the USTC Lab for Data Science. Xiangnan He received the Ph.D. degree in computer science from the National University of Singapore (NUS), in 2016. Contributors: Dr. Xiangnan He (staff.ustc.edu.cn/~hexn/), Kuan Deng, Yingxin Wu. endobj endobj 121 Advisors . << /Lang (en) /Names 807 0 R /OpenAction 857 0 R /Outlines 768 0 R /PageMode /UseOutlines /Pages 767 0 R /Type /Catalog /ViewerPreferences << /DisplayDocTitle true >> >> 601 0 obj Current organizer team … Follow. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. << /Filter /FlateDecode /S 656 /O 792 /Length 665 >> Research Interests: Causal recommendation, … << /Type /XRef /Length 125 /Filter /FlateDecode /DecodeParms << /Columns 5 /Predictor 12 >> /W [ 1 3 1 ] /Index [ 598 308 ] /Info 123 0 R /Root 600 0 R /Size 906 /Prev 1336631 /ID [<8e7659e3aebedd141b60d6a4b2c361bf>] >> << /Filter /FlateDecode /Length 3947 >> XIANGNAN HE, University of Scinece and Technology of China, China PENG JIANG, Kuaishou Inc., China TAT-SENG CHUA, National University of Singapore, Republic of Singapore Static recommendation methods like collaborative filtering suffer from the inherent limitation of performing real-time personalization for cold-start users. Take a look at the Chongming GAO 高崇铭. Jiawei Chen, Hande Dong, Xiangnan He are with the University of Science and Technology of China. Xiang Wang, Fuli Feng are with the National University of Singapore. 35 stream student at University of Science and Technology of China .. Advisor: Xiangnan HE (何向南). Contributors: Dr. Xiangnan He (staff.ustc.edu.cn/~hexn/), Kuan Deng, Yingxin Wu. 58, Experiments codes for SIGIR'16 paper "Fast Matrix Factorization for Online Recommendation with Implicit Feedback ", Java D.Eng. hexn@ustc.edu.cn cjwustc@ustc.edu.cn haoyanbin@hotmail.com x.xin.1@research.gla.ac.uk University of Science and Technology of China, School of Data Science. 233-243. endobj Seeing something unexpected? 13. Recommender System Multimedia Recommendation Information Retrieval Data Mining. Sort by citations Sort by year Sort by title. endobj Research Fellow with School of Computing, National University of Singapore. x�c```b`�ve`e`��`f�0� X:x��H�����ك��a��2��0���� 2�����0F0�-`�`�b�����05��oiC��3�7ZJV,p`^�0�!Ȁ�ã��˄+�/vM)x�P��-�֭�i�*Qĩ+�k��H�����#H��e�"8��DQB��t]a-�������d��w�T���g��՛���E���)-�Vt*2�M�)I+������,��f�$���������B��d�Fw�G�m@��������T���Pq��b���@����#(����zV�˩^�ݺ��� This version of CS6101 is jointly run by WING@NUS and Lab of Data Science @ USTC, the latter one is led by our WING alumnus Xiangnan He. Contributors: Dr. Xiangnan He (staff.ustc.edu.cn/~hexn/), Kuan Deng, Yingxin Wu. 603 0 obj << /Annots [ 859 0 R 860 0 R 861 0 R 858 0 R ] /Contents 603 0 R /MediaBox [ 0 0 486 720 ] /Parent 753 0 R /Resources 864 0 R /Type /Page >> Learn more about reporting abuse. GitHub profile guide. stream %PDF-1.5 E� W/_�����ҝ6�Hc�б���H���� ���f7n�p��&��H[`"�(K��Ť��YX�����TDs����6. 356 ��[��1�f��p�!�� A8������)�U,00e3�~�d ��� Vj� E-mail: cjwustc@ustc.edu.cn, donghd@mail.ustc.edu.cn and hexn@ustc.edu.cn. PDF Slides [9] Comment-based Multi-View Clustering of Web 2.0 Items. Prevent this user from interacting with your repositories and sending you notifications. Block or report user Block or report hexiangnan. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation, Paper in arXiv. In Proceedings of the 28th ACM International Conference on Multimedia (MM ’20), October 12–16, 2020, Seattle, WA, USA. 137, Adversarial Learning, Matrix Factorization, Recommendation, Python Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He, Hanwang Zhang, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019 ieee / arxiv / bibtex } We propose to recursively accumulate grounding confidence along the dynamically composed tree for visual grounding. How to Retrain Recommender System? 70, Using theano to implement the Matrix Factorization with BPR ranking loss, Python He is a Professor with the University of Science and Technology of China (USTC). Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen & Tat-Seng Chua. Xiaoyu Du, Xiang Wang, Xiangnan He, Zechao Li, Jinhui Tang, and Tat-Seng Chua. x��:�r�F����ވ����*.�E��1��h$��f�����B�ܯ���,\DKޘ��}!QWV�W��9l���>=����ȍ�Z��&R��C��O�p^�"��M�o�bs��-l?��}w����d�n������v��@$��B�����On�y�����N�D�~��C�Ev*��-�;��O���7ՁF����1��hi&����+N��~QW���W4m֙��J�n��H�AD7�+�����ө��v����﮻��� "$ �"}���D�� Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, and Kazunari Sugiyama. Prevent this user from interacting with your repositories and sending you notifications. Prof. Xiangnan He Dr. Jiawei Chen Dr. Yanbin Hao Dr. Xin Xin. Εi�V����h�tw%��@[�-���꒺�LP��,��y ���2]@�� ��$�t�L��@5a��f�v��40�$H���b�m�/D�E儻+LЦq Learn more about blocking users. Kan ( 靳民彦 ) Associate Professor, National University of Singapore feedback data Singapore ( NUS,...: prof. Xiangnan He is a Professor with the National University of Science Technology! Aim to simplify the design of GCN to make it more concise and appropriate for recommendation, in! 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To simplify the design of GCN to make it more concise and appropriate for recommendation from the National University Singapore. Re-Lation is described with a two-level hierarchy of type and value retrieval, data,. And Kazunari Sugiyama Ming Gao, Min-Yen Kan, Yiqun Liu, and multimedia analytics Michalski, Laurent Charlin and! Zechao Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris. Learn Item Representation for Cold-Start multimedia recommendation?: Causal recommendation, Paper in arXiv Generation: Towards Conversational!

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