partition transparencygraph-centric algorithmsvertex-centric algorithmsGraph computations often have to be conducted in parallel on partitioned graphs. The choice of graph partitioning strategies, however, has strong impact on the design of graph computation algorithms. A graph algorithm developed under ...
We analyzed more than 20k advertisements in real estate websites to try to find underpriced houses with Graphext's predictive algorithms. Along the way we looked into the relationships between prices and factors such as education level or location index to try to find insights and patterns in th...
A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks. PADL 2017. paper Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna. Attention Solves Your TSP, Approximately. 2018. paper Wouter Kool, Herke van Hoof, Max Welling. Learning to Solve NP-Complete Problems...
Learning Steady-States of Iterative Algorithms over Graphs.ICML 2018.paper Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alex Smola, Le Song. Graph Capsule Convolutional Neural Networks.ICML 2018 Workshop.paper Saurabh Verma, Zhi-Li Zhang. Capsule Graph Neural Network.ICLR 2019.paper Zhang Xinyi, Lihui...
In this research, focused on development of algorithms for healthcare applications, we acknowledge the profound ethical implications and potential impacts on patient outcomes. While the technical evaluation of GLLA demonstrates its effectiveness, we recognize the crucial need to assess and mitigate potenti...
A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks. PADL 2017. paper Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna. Attention Solves Your TSP, Approximately. 2018. paper Wouter Kool, Herke van Hoof, Max Welling. Learning to Solve NP-Complete Problems...
graph algorithms is to run in adistributedsetting, i.e., to partition the data (and the algorithm) among multiple computers to perform the computation in parallel. While this approach allows one to process graphs with trillions of edges, it also introduces new challenges. Namely, because each ...
Learning Steady-States of Iterative Algorithms over Graphs. ICML 2018. paper Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alex Smola, Le Song. Graph Capsule Convolutional Neural Networks. ICML 2018 Workshop. paper Saurabh Verma, Zhi-Li Zhang. Capsule Graph Neural Network. ICLR 2019. paper Zhang Xiny...
Neural Execution of Graph Algorithms. ICLR 2020. paper Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell. GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR 2020. paper Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna. ...
A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks. PADL 2017. paper Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna. Attention Solves Your TSP, Approximately. 2018. paper Wouter Kool, Herke van Hoof, Max Welling. Learning to Solve NP-Complete Problems...