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Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions.
Factorization meets the neighborhood: A multifaceted collaborative filtering model
Yehuda Koren · 2008
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Factorization machines
Steffen Rendle · 2010
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Fast context-aware recommendations with factorization machines
Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, and Lars Schmidt-Thieme · 2011
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Factorization machines with libfm
Steffen Rendle · 2012
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Gradient boosting factorization machines
Chen Cheng, Fen Xia, Tong Zhang, Irwin King, and Michael R Lyu · 2014
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Comment-based multi-view clustering of web 2.0 items
Xiangnan He, Min-Yen Kan, Peichu Xie, and Xiao Chen · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Exploiting web images for semantic video indexing via robust sample-specific loss
Yang Yang, Zheng-Jun Zha, Yue Gao, Xiaofeng Zhu, and Tat-Seng Chua · 2014
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Frappe: Understanding the usage and perception of mobile app recommendations in-the-wild
Linas Baltrunas, Karen Church, Alexandros Karatzoglou, and Nuria Oliver · 2015
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The movielens datasets: History and context
F. Maxwell Harper and Joseph A. Konstan · 2015
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Core: Context-aware open relation extraction with factorization machines
Fabio Petroni, Luciano Del Corro, and Rainer Gemulla · 2015
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Supervised discrete hashing
Fumin Shen, Chunhua Shen, Wei Liu, and Heng Tao Shen · 2015
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Visual classification by l1-hypergraph modeling
Meng Wang, Xueliang Liu, and Xindong Wu · 2015
Cited alongside, same era.
Multitask spectral clustering by exploring intertask correlation
Yang Yang, Zhigang Ma, Yi Yang, Feiping Nie, and Heng Tao Shen · 2015
Cited alongside, same era.
Expert finding for question answering via graph regularized matrix completion
Zhou Zhao, Lijun Zhang, Xiaofei He, and Wilfred Ng · 2015
Cited alongside, same era.
Higher-order factorization machines
Mathieu Blondel, Akinori Fujino, Naonori Ueda, and Masakazu Ishihata · 2016
Cited alongside, same era.
Context-aware image tweet modelling and recommendation
Tao Chen, Xiangnan He, and Min-Yen Kan · 2016
Cited alongside, same era.
Wide & deep learning for recommender systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, et al · 2016
Cited alongside, same era.
Discrete collaborative filtering
Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan, and Tat-Seng Chua · 2016
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User Preference Learning for Online Social Recommendation
Zhou Zhao, Hanqing Lu, Deng Cai, Xiaofei He, and Yueting Zhuang · 2016
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A generic coordinate descent framework for learning from implicit feedback
Immanuel Bayer, Xiangnan He, Bhargav Kanagal, and Steffen Rendle · 2017
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Attentive collaborative filtering: Multimedia recommendation with feature- and item-level attention
Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat-Seng Chua · 2017
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SCA-CNN: spatial and channel-wise attention in convolutional networks for image captioning
Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, and Tat-Seng Chua · 2017
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BiRank: Towards ranking on bipartite graphs
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Fast matrix factorization for online recommendation with implicit feedback
Xiangnan He, Hanwang Zhang, Min-Yen Kan, and Tat-Seng Chua · 2016
Cited alongside, same era.
Field-aware factorization machines for ctr prediction
Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, and Chih-Jen Lin · 2016
Cited alongside, same era.
Deep crossing: Web-scale modeling without manually crafted combinatorial features
Ying Shan, T Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, and JC Mao · 2016
Cited alongside, same era.
Scalable semi-supervised learning by efficient anchor graph regularization
Meng Wang, Weijie Fu, Shijie Hao, Dacheng Tao, and Xindong Wu · 2016
Cited alongside, same era.
Learning from collective intelligence: Feature learning using social images and tags
Hanwang Zhang, Xindi Shang, Huanbo Luan, Meng Wang, and Tat-Seng Chua · 2016
Cited alongside, same era.
Xiangnan He, Ming Gao, Min-Yen Kan, and Dingxian Wang · 2017
Closest in time.
Neural collaborative filering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua · 2017
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Neural factorization machines for sparse predictive analytics
Xiangnan He and Tat-Seng Chua · 2017
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Item Silk Road: Recommending Items from Information Domains to Social Users
Xiang Wang, Xiangnan He, Liqiang Nie and Tat-Seng Chua · 2017
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Learning on big graph: Label inference and regularization with anchor hierarchy
Meng Wang, Weijie Fu, Shijie Hao, Hengchang Liu, and Xindong Wu · 2017
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Learning to attend and to rank with word-entity duets
Chenyan Xiong, Jimie Callan, and Tie-Yen Liu · 2017
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Visual translation embedding network for visual relation detection
Hanwang Zhang, Zawlin Kyaw, Shih-Fu Chang, and Tat-Seng Chua · 2017
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