Solving machine learning with machine learning: Exploiting Very Large-Scale Neighbourhood Search for synthesizing machine learning pipelines

This paper presents a comparative study of multiple algorithms that can be used to automatically search for high-performing pipelines on machine learning problems. These algorithms, namely Very Large-Scale Neighbourhood search (VLSN), Breadth-first search, Metropolis-Hastings, Monte-Carlo tree search (MCTS), enumerative A* search, and Genetic...

Evolving a Search Procedure for Program Synthesis

In recent months, researchers developed several new search procedures to augment the process of program synthesis. While many of them performed better than their predecessors, the proposed solutions are still far from ideal. One possible way of overcoming the shortcomings of single search methods is employing genetic algorithms, which have been...