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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 531–540 of 641 papers

TitleStatusHype
FairAutoML: Embracing Unfairness Mitigation in AutoML—0
Fair AutoML Through Multi-objective Optimization—0
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation—0
Fast Data Aware Neural Architecture Search via Supernet Accelerated Evaluation—0
FDNAS: Improving Data Privacy and Model Diversity in AutoML—0
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures—0
Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop—0
Floralens: a Deep Learning Model for the Portuguese Native Flora—0
FRAMED: An AutoML Approach for Structural Performance Prediction of Bicycle Frames—0
Generating Diverse Synthetic Datasets for Evaluation of Real-life Recommender Systems—0
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All datasetsChalearn-AutoML-1Breast Cancer Coimbra Data SetOrdinalDatasetWine

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4—Unverified
2reference_mbRank (AutoML5)5.2—Unverified
3postech.mlg_exbrainRank (AutoML5)5.2—Unverified
4abhishek4Rank (AutoML5)4.6—Unverified
5referenceRank (AutoML5)4.4—Unverified
6reference_lsRank (AutoML5)4—Unverified
7djajeticRank (AutoML5)3—Unverified
8aad_freiburgRank (AutoML5)1.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02—Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33—Unverified