48 citations · 123 across the 5 of their papers we have counts for
5 papers
Meta-Learning for Symbolic Hyperparameter Defaults
Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn +2
Hyperparameter optimization in machine learning (ML) deals with the problem of empirically learning an optimal algorithm configuration from data, usually formulated as a black-box…
GAMA: a General Automated Machine learning Assistant
Pieter Gijsbers, Joaquin Vanschoren
The General Automated Machine learning Assistant (GAMA) is a modular AutoML system developed to empower users to track and control how AutoML algorithms search for optimal machine…
OpenML-Python: an extensible Python API for OpenML
Matthias Feurer, Jan N. van Rijn, Arlind Kadra +6
OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper we introduce Open…
An Open Source AutoML Benchmark
Pieter Gijsbers, Erin LeDell, Janek Thomas +3
In recent years, an active field of research has developed around automated machine learning (AutoML). Unfortunately, comparing different AutoML systems is hard and often done inco…
Layered TPOT: Speeding up Tree-based Pipeline Optimization
Pieter Gijsbers, Joaquin Vanschoren, Randal S. Olson
With the demand for machine learning increasing, so does the demand for tools which make it easier to use. Automated machine learning (AutoML) tools have been developed to address…