We demonstrate a speed-up of several orders of magnitude when predicting word similarity by vector operations on our embeddings as opposed to directly computing ...

Jun 17, 2019 · We explore dense vector representations as an effective way to approximate the same information: we introduce a simple yet efficient and effective approach for ...

We represent nodes in a graph with dense embeddings that are good in approximating such custom, e.g. application-specific, pairwise node similarity measures.

This work introduces a simple yet efficient and effective approach for learning graph embeddings that takes structural measures of pairwise node ...

Sep 17, 2019 · PDF | On Jan 1, 2019, Andrey Kutuzov and others published Making Fast Graph-based Algorithms with Graph Metric Embeddings | Find, read and ...

Making Fast Graph-based Algorithms with Graph Metric Embeddings. Path2vec is a new approach for learning graph embeddings that relies on structural measures ...

Making Fast Graph-based Algorithms with Graph Metric Embeddings · Learning Graph Embeddings from WordNet-based Similarity Measures.

Nov 20, 2021 · In this post, I am going to walk through an example of how to tune the FastRP hyperparameters to a given node classification problem using Optuna.

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Mohammad Dorgham's 4 research works with 18 citations, including: Making Fast Graph-based Algorithms with Graph Metric Embeddings.