AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Por um escritor misterioso
Last updated 22 dezembro 2024
This paper studies the problem of finding graphs that maximize the number of edges, while avoiding short cycles. It formulates graph generation as a reinforcement learning task, and compares methods like AlphaZero and tabu search. A key finding is that using a curriculum - building larger graphs from good smaller graphs - significantly improves performance. The work makes progress on an open problem in extremal graph theory.
Petar Veličković on LinkedIn: Building Google Maps' Algorithm & AI Research at Google Deepmind - The…
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Petar Veličković - CatalyzeX
A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment
Adam Zsolt Wagner
Adam Zsolt Wagner
AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
Tabu Search — AI Search Algorithms for Smart Mobility
graphml - Telegram channel posts - Graph Machine Learning - Telemetrio
Petar Veličković on LinkedIn: #icml2023
Evolutionary binary feature selection using adaptive ebola optimization search algorithm for high-dimensional datasets
AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search
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