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graph partitioning

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PyTorch-BigGraph: A Large-scale Graph Embedding System

28 Mar 2019facebookresearch/PyTorch-BigGraph

Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks.

GRAPH EMBEDDING GRAPH PARTITIONING LINK PREDICTION

Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting

24 Sep 2019liyaguang/DCRNN

For the first time, we forecast the traffic of the entire California highway network with 11, 160 traffic sensor locations simultaneously.

GRAPH PARTITIONING

Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters

KDD 2017 benedekrozemberczki/karateclub

More precisely, our framework works in two steps: a local ego-net analysis phase, and a global graph partitioning phase .

 SOTA for Community Detection on Amazon (NMI metric )

COMMUNITY DETECTION GRAPH PARTITIONING

Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning

24 Jan 2018NervanaSystems/ngraph-python

The current approach, which we call "direct optimization", requires deep changes within each framework to improve the training performance for each hardware backend (CPUs, GPUs, FPGAs, ASICs) and requires $\mathcal{O}(fp)$ effort; where $f$ is the number of frameworks and $p$ is the number of platforms.

GRAPH PARTITIONING

Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community Structure

SEA 2017 2017 SebastianSchlag/kahypar

We present an improved coarsening process for multilevel hypergraph partitioning that incorporates global information about the community structure.

COMMUNITY DETECTION GRAPH PARTITIONING HYPERGRAPH PARTITIONING

Towards Efficient Large-Scale Graph Neural Network Computing

19 Oct 2018xchadesi/GraphNeuralNetwork

This evolution has led to large graph-based irregular and sparse models that go beyond what existing deep learning frameworks are designed for.

GRAPH PARTITIONING KNOWLEDGE GRAPHS

Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted Multicuts

25 May 2019constantinpape/cluster_tools

The throughput of electron microscopes has increased significantly in recent years, enabling detailed analysis of cell morphology and ultrastructure.

GRAPH PARTITIONING INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Learning Space Partitions for Nearest Neighbor Search

24 Jan 2019twistedcubic/learn-to-hash

Space partitions of $\mathbb{R}^d$ underlie a vast and important class of fast nearest neighbor search (NNS) algorithms.

GRAPH PARTITIONING QUANTIZATION

Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching

NeurIPS 2019 HongtengXu/s-gwl

Using this concept, we extend our method to multi-graph partitioning and matching by learning a Gromov-Wasserstein barycenter graph for multiple observed graphs; the barycenter graph plays the role of the disconnected graph, and since it is learned, so is the clustering.

GRAPH MATCHING GRAPH PARTITIONING

The Product Cut

NeurIPS 2016 xbresson/pcut

We introduce a theoretical and algorithmic framework for multi-way graph partitioning that relies on a multiplicative cut-based objective.

GRAPH PARTITIONING