I recently travelled to Marrakech, Morocco, to present my research at the 9th International Conference on Metaheuristics and Nature-Inspired Computing (META 2023). Held from November 1–4, 2023, the conference provided an incredible atmosphere for discussing how meta-heuristics can tackle complex optimisation problems.
My paper, “Machine learning-based per-instance algorithm selection for high-performance subgraph isomorphism enumeration,” addresses a classic “needle in a haystack” problem: finding small patterns (subgraphs) within massive data graphs.
In graph analytics, no single algorithm is the fastest for every problem instance. My research proposes a metaheuristic approach that uses Machine Learning (ML) to predict the fastest algorithm for a specific graph pair.
Find the paper on Pure below:
