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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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2 results for “Ego-Graphs”

Transfer Learning of Graph Neural Networks with Ego-graph Information Maximizationcs.LG

This work improves GNN training efficiency by maximizing ego-graph information.

problem Training dedicated GNNs is costly for large-scale graphs.

method Proposes EGI (Ego-Graph Information maximization) to capture essential graph information and establish a theoretical framework for transfer learning.

result Demonstrates the effectiveness of EGI in improving GNN training efficiency and transferability.

Graph Neural Networks Transfer Learning Ego-Graph Information Local Graph Laplacians Synthetic Experiments

2020-09-11abs ↗pdf ↗

Spectral Greedy Coresets for Graph Neural Networkscs.LG

This paper develops a coreset method for GNNs that speeds up training on large graphs.

problem Training Graph Neural Networks (GNNs) on large-scale graphs is computationally expensive.

method The paper proposes a spectral greedy coreset (SGGC) method that selects ego-graphs based on spectral embeddings.

result SGGC significantly speeds up GNN training on large graphs and outperforms other coreset methods.

Graph Neural Networks Graph Coresets Large Graphs Spectral Embedding Ego-Graphs

2024-05-27abs ↗pdf ↗