Predicting Path Failure In Time-Evolving Graphs
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Hong Cheng | Jia Li | Pengyun Wang | Lujia Pan | Jianfeng Zhang | Jiao Su | Zhichao Han | Hong Cheng | Lujia Pan | Jianfeng Zhang | Zhichao Han | Jia Li | Pengyun Wang | Jiao Su
[1] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[2] Charu C. Aggarwal,et al. On Node Classification in Dynamic Content-based Networks , 2011, SDM.
[3] Zehra Cataltepe,et al. GA-TVRC-Het: genetic algorithm enhanced time varying relational classifier for evolving heterogeneous networks , 2014, Data Mining and Knowledge Discovery.
[4] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[5] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[6] Andreas Christmann,et al. Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.
[7] Eleni I. Vlahogianni,et al. Short-term traffic forecasting: Where we are and where we’re going , 2014 .
[8] Cheng Li,et al. DeepCas: An End-to-end Predictor of Information Cascades , 2016, WWW.
[9] Max Welling,et al. Modeling Relational Data with Graph Convolutional Networks , 2017, ESWC.
[10] Heikki Mannila,et al. Rule Discovery in Telecommunication Alarm Data , 1999, Journal of Network and Systems Management.
[11] Bowen Zhou,et al. A Structured Self-attentive Sentence Embedding , 2017, ICLR.
[12] Steven Skiena,et al. DeepWalk: online learning of social representations , 2014, KDD.
[13] J. Yosinski,et al. Time-series Extreme Event Forecasting with Neural Networks at Uber , 2017 .
[14] Kevin Chen-Chuan Chang,et al. Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding , 2017, AAAI.
[15] Donald J. Berndt,et al. Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.
[16] Cyrus Shahabi,et al. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting , 2017, ICLR.
[17] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[18] Alberto Sillitti,et al. Failure prediction based on log files using Random Indexing and Support Vector Machines , 2013, J. Syst. Softw..
[19] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[20] Lars Grunske,et al. Hora: Architecture-aware online failure prediction , 2017, J. Syst. Softw..
[21] Yu Zheng,et al. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction , 2016, AAAI.
[22] Hong Cheng,et al. Semi-Supervised Graph Classification: A Hierarchical Graph Perspective , 2019, WWW.
[23] Zhanxing Zhu,et al. Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting , 2017, IJCAI.