Semanlink - WORKSHOP: BigNet @ WWW 2018 Workshop on Learning Representations for Big Networks

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sl:creationDate : 2018-01-27
sl:creationTime : 2018-01-27T15:13:16Z

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Network representation learning (NRL): Approaches that automatically learn to encode network structure into low-dimensional embeddings, using techniques based on deep learning and nonlinear dimensionality reduction

**Goal of representation learning for networks: efficient task-independant feature learning for ML in networks.** But it's hard. DL toolbox are designed for single sequences or grids (for instance CNN for images, RNN or word2vec are fixed size), but networks are far more complex!

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