AutoML

Automated Machine Learning (AutoML) is a general concept which covers diverse techniques for automated model learning including automatic data preprocessing, architecture search, and model selection. Source: Evaluating recommender systems for AI-driven data science (1905.09205)

Source: CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 371–380 of 641 papers

Title	Date	Tasks	Status
Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A data-driven approach to Predict Brain Age from Cortical Anatomical Measures	Oct 8, 2019	AutoMLBIG-bench Machine Learning	—Unverified
Analysis of the AutoML Challenge Series 2015–2018	May 18, 2019	AutoMLBIG-bench Machine Learning	—Unverified
An Approach for Efficient Neural Architecture Search Space Definition	Oct 25, 2023	AutoMLNeural Architecture Search	—Unverified
An Automated Machine Learning (AutoML) Method for Driving Distraction Detection Based on Lane-Keeping Performance	Mar 10, 2021	AutoMLBayesian Optimization	—Unverified
Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization	Jan 7, 2021	Active LearningAutoML	—Unverified
An AutoML-based approach for Network Intrusion Detection	Nov 24, 2024	AutoMLFeature Engineering	—Unverified
An AutoML-based Approach to Multimodal Image Sentiment Analysis	Feb 16, 2021	AutoMLMarketing	—Unverified
A New Deep Neural Architecture Search Pipeline for Face Recognition	May 12, 2020	AutoMLFace Recognition	—Unverified
An experimental survey and Perspective View on Meta-Learning for Automated Algorithms Selection and Parametrization	Apr 8, 2025	AutoMLMeta-Learning	—Unverified
An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version)	Sep 16, 2020	AutoMLBIG-bench Machine Learning	—Unverified

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All datasets Chalearn-AutoML-1 Breast Cancer Coimbra Data Set OrdinalDataset Wine

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	marc.boulle	Rank (AutoML5)	6.4	—	Unverified
2	reference_mb	Rank (AutoML5)	5.2	—	Unverified
3	postech.mlg_exbrain	Rank (AutoML5)	5.2	—	Unverified
4	abhishek4	Rank (AutoML5)	4.6	—	Unverified
5	reference	Rank (AutoML5)	4.4	—	Unverified
6	reference_ls	Rank (AutoML5)	4	—	Unverified
7	djajetic	Rank (AutoML5)	3	—	Unverified
8	aad_freiburg	Rank (AutoML5)	1.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Logistic Regression	Accuracy	97.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Zero-shot-BERT-SORT	1:1 Accuracy	55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Logistic Regression	accuracy	98.33	—	Unverified