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 201–210 of 641 papers

Title	Date	Tasks	Status
Data Augmentation of Multivariate Sensor Time Series using Autoregressive Models and Application to Failure Prognostics	Oct 21, 2024	AutoMLData Augmentation	—Unverified
Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims	Jul 22, 2021	AutoMLBenchmarking	—Unverified
An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version)	Sep 16, 2020	AutoMLBIG-bench Machine Learning	—Unverified
Bit-Mixer: Mixed-precision networks with runtime bit-width selection	Mar 31, 2021	AutoMLBinarization	—Unverified
Auto Machine Learning for Medical Image Analysis by Unifying the Search on Data Augmentation and Neural Architecture	Jul 21, 2022	AutoMLData Augmentation	—Unverified
Bringing Quantum Algorithms to Automated Machine Learning: A Systematic Review of AutoML Frameworks Regarding Extensibility for QML Algorithms	Oct 6, 2023	AutoMLBenchmarking	—Unverified
Adaptive Bayesian Linear Regression for Automated Machine Learning	Apr 1, 2019	AutoMLBayesian Optimization	—Unverified
BUSU-Net: An Ensemble U-Net Framework for Medical Image Segmentation	Mar 3, 2020	AutoMLImage Segmentation	—Unverified
Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark	Sep 3, 2020	AutoMLBIG-bench Machine Learning	—Unverified
Benchmarking Automated Machine Learning Methods for Price Forecasting Applications	Apr 28, 2023	AutoMLBenchmarking	—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