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PHH_Graph_Representation_Learning_11092020
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phanhoang17
September 11, 2020
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PHH_Graph_Representation_Learning_11092020
phanhoang17
September 11, 2020
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Transcript
Graph Representation Learning An introduction Phan Hoang - AI Research
Team
Do we need deep graph neural network?
Graph Representation Learning?!
Graph Representation Learning?! - Viblo recommender engine - Graph-based recommender
system for paper citation network - https://api.semanticscholar.org/v1/paper/arXiv:2006.07739 - https://jsoneditoronline.org/#left=cloud.f3946e860ca54e98934899f6f30eb475 - https://www.connectedpapers.com/
Graph Representation Learning?!
Graph Representation Learning?!
Prerequisite knowledge - https://viblo.asia/p/6J3ZgP0qlmB#_1-so-ly-thuyet-do-thi-co-ban-1
Tasks - https://viblo.asia/p/6J3ZgP0qlmB#_1-so-bai-toan-dien-hinh-2 - Node Classification - Link Prediction -
Graph Clustering & community detection - ...
Node Embedding - Random Walk / DeepWalk - Word2Vec
Node Embedding - Random Walk
Node Embedding - Skip-gram model
DeepWalk - karate dataset
Node Embedding - Cons - Unseen node? - Node feature?
- Tranductive learning vs inductive learning
Graph Neural Network - an introduction
Example of GCN model
Example of GCN model
Graph Convolution Network - Kipf (2016)
GraphSage - L.Hamilton (2017)
GraphSage - L.Hamilton (2017)
GraphSage - inductive learning
The number of layers
GraphSage - L.Hamilton (2017) - Loss function, un-supervised learning
How to apply?
Real use-case applications - PinSage / UberEat
Real use-case applications - PinSage / UberEat - Based on
GraphSage paper (Haminton / 2017) - Heterogeneous graph / bipartite graph - Node Embedding: image + text feature, user info - Edge: Pin-Board, User-Dish, User-Restaurant relation
Real use-case applications - Decagon
Real use-case applications - Decagon
Real use-case applications - Goal-directed generation
How to model the GNN for a specific dataset?
Task: Text Classification
Task: Relation Extraction / NLP
Task: Key-Information Extraction
Task: Recommender System
Other tasks - 3D Object Detection - Action Recognition /
Pose Estimation - GAN / VAE - GAT / Graph Transformer - Feature Matching - Key Information Extraction - Scene Graph Generation - Recommender System - ...
Papers - Cluster-GCN / GraphSAINT - graph/sub-graph/node sampling - GAT
(graph attention network) - GIN (graph isomorphism network) - Deep-GCN / Deeper-GCN - going deeper with GCN - ...
Cons - non-injective aggregate function
Cons - adversarial attack
Thank you! https://viblo.asia/p/deep-learning-graph-neural-network-a-literature-review-and-applications-6J3ZgP0qlmB