SOTAVerified

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

Showing 311320 of 641 papers

TitleStatusHype
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement0
AutoML for Deep Recommender Systems: A Survey0
Meta-Learning of NAS for Few-shot Learning in Medical Image Applications0
Privacy-preserving Online AutoML for Domain-Specific Face Detection0
Deep AutoAugmentCode1
Model-free feature selection to facilitate automatic discovery of divergent subgroups in tabular data0
Automated Machine Learning: A Case Study on Non-Intrusive Appliance Load Monitoring0
AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance0
XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine LearningCode1
Mining Robust Default Configurations for Resource-constrained AutoML0
Show:102550
← PrevPage 32 of 65Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4Unverified
2reference_mbRank (AutoML5)5.2Unverified
3postech.mlg_exbrainRank (AutoML5)5.2Unverified
4abhishek4Rank (AutoML5)4.6Unverified
5referenceRank (AutoML5)4.4Unverified
6reference_lsRank (AutoML5)4Unverified
7djajeticRank (AutoML5)3Unverified
8aad_freiburgRank (AutoML5)1.6Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33Unverified