AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

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.

AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

Petar Veličković on LinkedIn: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment

Adam Zsolt Wagner

AI/ML: Data Trojan Horse - by Rayfe Gaspar-Asaoka

A new hyper-heuristic based on ant lion optimizer and Tabu search algorithm for replica management in cloud environment

AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

Juan (@jeandut14000) / X

AI Summary: Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

Immunity-based Ebola optimization search algorithm for minimization of feature extraction with reduction in digital mammography using CNN models

graphml - Telegram channel posts - Graph Machine Learning - Telemetrio

Petar Veličković on LinkedIn: #icml2023