Feb 10, 2019 · We propose a new scalable technique for the multidimensional balanced graph partitioning problem. The method is based on applying randomized projected gradient ...

We propose a new scalable technique for the multidimensional balanced graph partitioning problem. It is based on applying randomized projected gradient descent.

ABSTRACT. Motivated by performance optimization of large-scale graph processing systems that distribute the graph across multi-.

It is based on applying randomized projected gradient descent to a non- convex continuous relaxation of the objective. We show how to implement the new ...

We propose a new scalable technique for the multidimensional balanced graph partitioning problem. It is based on applying randomized projected gradient descent ...

Aug 28, 2020 · (Ads) Our paper: "Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent", where we used gradient descent to find ...

Multi-dimensional balanced graph partitioning via projected gradient descent. D Avdiukhin, S Pupyrev, G Yaroslavtsev. arXiv preprint arXiv:1902.03522, 2019. 21 ...

“Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent”: KDD 2019: Talk: “Adversarially Robust Submodular Maximization under Knapsack ...

Jun 14, 2018 · BalAnceD GRaph Partitioining via. RAndoMized Projected Gradient DEscent. •. ∗. If fractional values remain, use them as rounding probabilities.

Sep 16, 2022 · We propose a unified principle to achieve balanced graph partitioning and instantiate it with two balanced graph par- tition algorithms. • To ...