145 citations · 793 across the 36 of their papers we have counts for
5 papers · 1 filter
EBIC: an open source software for high-dimensional and big data biclustering analyses
Patryk Orzechowski, Jason H. Moore
Motivation: In this paper we present the latest release of EBIC, a next-generation biclustering algorithm for mining genetic data. The major contribution of this paper is adding su…
Learning concise representations for regression by evolving networks of trees
William La Cava, Tilak Raj Singh, James Taggart +2
We propose and study a method for learning interpretable representations for the task of regression. Features are represented as networks of multi-type expression trees comprised o…
Gamorithm
Moshe Sipper, Jason H. Moore
Examining games from a fresh perspective we present the idea of game-inspired and game-based algorithms, dubbed "gamorithms".
Where are we now? A large benchmark study of recent symbolic regression methods
Patryk Orzechowski, William La Cava, Jason H. Moore
In this paper we provide a broad benchmarking of recent genetic programming approaches to symbolic regression in the context of state of the art machine learning approaches. We use…
EBIC: an evolutionary-based parallel biclustering algorithm for pattern discover
Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang +1
In this paper a novel biclustering algorithm based on artificial intelligence (AI) is introduced. The method called EBIC aims to detect biologically meaningful, order-preserving pa…