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Found 6 papers, 2 papers with code
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs
Dynamic graph representation learning plays a crucial role in understanding evolving behaviors.
Two Layer Walk: A Community-Aware Graph Embedding
Community structures are critical for understanding the mesoscopic organization of networks, bridging local and global patterns.
Deep Insights into Automated Optimization with Large Language Models and Evolutionary Algorithms
Since this synergy enables a more efficient and creative search process, we first conduct an extensive review of recent research on the application of LLMs in optimization.
AutoRNet: Automatically Optimizing Heuristics for Robust Network Design via Large Language Models
Achieving robust networks is a challenging problem due to its NP-hard nature and complex solution space.
GraphEx: A Graph-based Extraction Method for Advertiser Keyphrase Recommendation
Online sellers and advertisers are recommended keyphrases for their listed products, which they bid on to enhance their sales.
Extreme Multi-Label Classification
MUlTI-LABEL-ClASSIFICATION
Exploring Knowledge Transfer in Evolutionary Many-task Optimization: A Complex Network Perspective
The field of evolutionary many-task optimization (EMaTO) is increasingly recognized for its ability to streamline the resolution of optimization challenges with repetitive characteristics, thereby conserving computational resources.
