EDGES: An Efficient Distributed Graph Embedding System on GPU Clusters
暂无分享,去创建一个
[1] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[2] Jian Pei,et al. Asymmetric Transitivity Preserving Graph Embedding , 2016, KDD.
[3] Tao Wang,et al. Image Classification at Supercomputer Scale , 2018, ArXiv.
[4] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[5] Lise Getoor,et al. Collective Classification in Network Data , 2008, AI Mag..
[6] Steven Skiena,et al. DeepWalk: online learning of social representations , 2014, KDD.
[7] Jian Tang,et al. GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding , 2019, WWW.
[8] Geoffrey E. Hinton,et al. A Scalable Hierarchical Distributed Language Model , 2008, NIPS.
[9] Alex Smola,et al. Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs , 2019, ArXiv.
[10] Mingzhe Wang,et al. LINE: Large-scale Information Network Embedding , 2015, WWW.
[11] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[12] Jure Leskovec,et al. Defining and evaluating network communities based on ground-truth , 2012, Knowledge and Information Systems.
[13] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[14] Qiongkai Xu,et al. GraRep: Learning Graph Representations with Global Structural Information , 2015, CIKM.
[15] Alexander J. Smola,et al. Distributed large-scale natural graph factorization , 2013, WWW.
[16] Alexander Peysakhovich,et al. PyTorch-BigGraph: A Large-scale Graph Embedding System , 2019, SysML.
[17] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[18] John C. Duchi,et al. Distributed delayed stochastic optimization , 2011, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[19] Jon M. Kleinberg,et al. The link-prediction problem for social networks , 2007, J. Assoc. Inf. Sci. Technol..
[20] Krishna P. Gummadi,et al. Measurement and analysis of online social networks , 2007, IMC '07.
[21] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[22] Jan Eric Lenssen,et al. Fast Graph Representation Learning with PyTorch Geometric , 2019, ArXiv.
[23] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[24] Jure Leskovec,et al. Predicting multicellular function through multi-layer tissue networks , 2017, Bioinform..
[25] Yizhou Sun,et al. Personalized entity recommendation: a heterogeneous information network approach , 2014, WSDM.
[26] H. Howie Huang,et al. G-Store: High-Performance Graph Store for Trillion-Edge Processing , 2016, SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.
[27] Stephen J. Wright,et al. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent , 2011, NIPS.
[28] Sebastiano Vigna,et al. The Graph Structure in the Web - Analyzed on Different Aggregation Levels , 2015, J. Web Sci..
[29] Yoshua Bengio,et al. Hierarchical Probabilistic Neural Network Language Model , 2005, AISTATS.
[30] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[31] Alexander J. Smola,et al. Scaling Distributed Machine Learning with the Parameter Server , 2014, OSDI.
[32] Jure Leskovec,et al. node2vec: Scalable Feature Learning for Networks , 2016, KDD.
[33] Jure Leskovec,et al. Representation Learning on Graphs: Methods and Applications , 2017, IEEE Data Eng. Bull..