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. 598 0 obj 35 Sort. student at University of Science and Technology of China .. Advisor: Xiangnan HE (何向南). 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. E-mail: cjwustc@ustc.edu.cn, donghd@mail.ustc.edu.cn and hexn@ustc.edu.cn. 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. You signed in with another tab or window. 356 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. Xiangnan He Sampling strategies have been widely applied in many recommendation systems to accelerate model learning from implicit feedback data. Xiangnan He, Kuan Deng ,Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang(2020). ACM, New "Yրɵ`�+��`r1���w�����.�F�Qr��&�;w��0J�q���a��$ Gv: Chongming GAO 高崇铭. hexn@ustc.edu.cn cjwustc@ustc.edu.cn haoyanbin@hotmail.com x.xin.1@research.gla.ac.uk My research interests span information retrieval, data mining, and multi-media analytics. Title. ��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�����)��� Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. Xiangnan He School of Information Science and Technology, USTC xiangnanhe@gmail.com Yongfeng Zhang Department of Computer Science Rutgers University … ��[��1�f��p�!�� A8������)�U,00e3�~�d ��� Vj� << /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>] >> 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. 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