Search Results for author: Mikel Landajuela Larma

Found 4 papers, 2 papers with code

Improving exploration in policy gradient search: Application to symbolic optimization

1 code implementation19 Jul 2021 Mikel Landajuela Larma, Brenden K. Petersen, Soo K. Kim, Claudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol

Many machine learning strategies designed to automate mathematical tasks leverage neural networks to search large combinatorial spaces of mathematical symbols.

Symbolic Regression

Distilling Wikipedia mathematical knowledge into neural network models

no code implementations13 Apr 2021 Joanne T. Kim, Mikel Landajuela Larma, Brenden K. Petersen

Machine learning applications to symbolic mathematics are becoming increasingly popular, yet there lacks a centralized source of real-world symbolic expressions to be used as training data.

BIG-bench Machine Learning Philosophy +2

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