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 601–610 of 641 papers

Title	Date	Tasks	Status
DeepFreak: Learning Crystallography Diffraction Patterns with Automated Machine Learning	Apr 26, 2019	AutoMLBIG-bench Machine Learning	CodeCode Available
Benchmark and Survey of Automated Machine Learning Frameworks	Apr 26, 2019	AutoMLBIG-bench Machine Learning	CodeCode Available
CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification	Apr 23, 2019	AutoMLGeneral Classification	—Unverified
Neural Architecture Search for Deep Face Recognition	Apr 21, 2019	AutoMLFace Recognition	—Unverified
Adaptive Bayesian Linear Regression for Automated Machine Learning	Apr 1, 2019	AutoMLBayesian Optimization	—Unverified
Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML	Mar 20, 2019	AutoMLContinual Learning	—Unverified
AutoML @ NeurIPS 2018 challenge: Design and Results	Mar 12, 2019	AutoMLBIG-bench Machine Learning	—Unverified
Continual Learning in Practice	Mar 12, 2019	AutoMLBIG-bench Machine Learning	—Unverified
SAFE ML: Surrogate Assisted Feature Extraction for Model Learning	Feb 28, 2019	AutoMLFeature Engineering	CodeCode Available
AutoQ: Automated Kernel-Wise Neural Network Quantization	Feb 15, 2019	AutoMLDeep Reinforcement 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