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Graph Convolutional Matrix Completion

Graph Convolutional Matrix CompletionRianne van den BergUniversity of AmsterdamAmsterdam, The N. KipfUniversity of AmsterdamAmsterdam, The Welling University of AmsterdamAmsterdam, The consider Matrix Completion for recommender systems from thepoint of view of link prediction on graphs. Interaction data suchas movie ratings can be represented by a bipartite user-item graphwith labeled edges denoting observed ratings. This representationis especially useful in the setting where additional Graph -based sideinformation is present. Building on recent progress in deep learn-ing on Graph -structured data, we propose a Graph auto-encoderframework based on differentiable message passing on the bipar-tite interaction Graph .

The decoder model is a pairwise decoder Aˇ = д(Z), which takes pairs of node embeddings (zi,zj)and predicts entries Aˇ ... Graph Convolutional Matrix Completion KDD’18 Deep Learning Day, August 2018, London, UK.

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  Decoder, Matrix, Deep, Completion, Graph, Convolutional, Graph convolutional matrix completion

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Collaborative Knowledge Base Embedding for Recommender …

www.kdd.org

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Structural Deep Network Embedding - SIGKDD

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Structural Deep Network Embedding Daixin Wang1, Peng Cui1, Wenwu Zhu1 1Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology, Tsinghua University. Beijing, China dxwang0826@gmail.com,cuip@tsinghua.edu.cn,wwzhu@tsinghua.edu.cn

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Deep Crossing: Web-Scale Modeling without Manually …

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gradient tree boosting [10]1 is one technique that shines in many applications. Tree boosting has been shown to give state-of-the-art results on many standard classi cation benchmarks [16]. LambdaMART [5], a variant of tree boost-ing for ranking, achieves state-of-the-art result for ranking 1Gradient tree boosting is also known as gradient boosting

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argue that explaining predictions is an important aspect in getting humans to trust and use machine learning e ectively, if the explanations are faithful and intelligible. The process of explaining individual predictions is illus-trated in Figure 1. It is clear that a doctor is much better positioned to make a decision with the help of a model if

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Fake News Detection on Social Media: A Data Mining …

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