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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

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

Memetic Multilevel Hypergraph Partitioning

GECCO 2018 2018 SebastianSchlag/kahypar

Hypergraph partitioning has a wide range of applications such as VLSI design or scientific computing.

GRAPH PARTITIONING HYPERGRAPH PARTITIONING

Network Flow-Based Refinement for Multilevel Hypergraph Partitioning

SEA 2018 2018 SebastianSchlag/kahypar

We present a refinement framework for multilevel hypergraph partitioning that uses max-flow computations on pairs of blocks to improve the solution quality of a k-way partition.

GRAPH PARTITIONING HYPERGRAPH PARTITIONING

Engineering a direct k-way Hypergraph Partitioning Algorithm

ALENEX 2017 2017 SebastianSchlag/kahypar

We also remove several further bottlenecks in processing large hyperedges, develop a faster contraction algorithm, and a new adaptive stopping rule for local search.

GRAPH PARTITIONING HYPERGRAPH PARTITIONING

k-way Hypergraph Partitioning via n-Level Recursive Bisection

ALENEX 2016 2017 SebastianSchlag/kahypar

We develop a multilevel algorithm for hypergraph partitioning that contracts the vertices one at a time.

GRAPH PARTITIONING HYPERGRAPH 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

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

KDD 2017 benedekrozemberczki/EgoSplitting

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

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 NEURAL NETWORK 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